Sample records for feature-based landmark information
-
Landmark-based deep multi-instance learning for brain disease diagnosis.
Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang
2018-01-01
In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.
-
Toward a model for lexical access based on acoustic landmarks and distinctive features
Stevens, Kenneth N.
2002-04-01
This article describes a model in which the acoustic speech signal is processed to yield a discrete representation of the speech stream in terms of a sequence of segments, each of which is described by a set (or bundle) of binary distinctive features. These distinctive features specify the phonemic contrasts that are used in the language, such that a change in the value of a feature can potentially generate a new word. This model is a part of a more general model that derives a word sequence from this feature representation, the words being represented in a lexicon by sequences of feature bundles. The processing of the signal proceeds in three steps: (1) Detection of peaks, valleys, and discontinuities in particular frequency ranges of the signal leads to identification of acoustic landmarks. The type of landmark provides evidence for a subset of distinctive features called articulator-free features (e.g., [vowel], [consonant], [continuant]). (2) Acoustic parameters are derived from the signal near the landmarks to provide evidence for the actions of particular articulators, and acoustic cues are extracted by sampling selected attributes of these parameters in these regions. The selection of cues that are extracted depends on the type of landmark and on the environment in which it occurs. (3) The cues obtained in step (2) are combined, taking context into account, to provide estimates of ``articulator-bound'' features associated with each landmark (e.g., [lips], [high], [nasal]). These articulator-bound features, combined with the articulator-free features in (1), constitute the sequence of feature bundles that forms the output of the model. Examples of cues that are used, and justification for this selection, are given, as well as examples of the process of inferring the underlying features for a segment when there is variability in the signal due to enhancement gestures (recruited by a speaker to make a contrast more salient) or due to overlap of gestures from
-
a Landmark Extraction Method Associated with Geometric Features and Location Distribution
Zhang, W.; Li, J.; Wang, Y.; Xiao, Y.; Liu, P.; Zhang, S.
2018-04-01
Landmark plays an important role in spatial cognition and spatial knowledge organization. Significance measuring model is the main method of landmark extraction. It is difficult to take account of the spatial distribution pattern of landmarks because that the significance of landmark is built in one-dimensional space. In this paper, we start with the geometric features of the ground object, an extraction method based on the target height, target gap and field of view is proposed. According to the influence region of Voronoi Diagram, the description of target gap is established to the geometric representation of the distribution of adjacent targets. Then, segmentation process of the visual domain of Voronoi K order adjacent is given to set up target view under the multi view; finally, through three kinds of weighted geometric features, the landmarks are identified. Comparative experiments show that this method has a certain coincidence degree with the results of traditional significance measuring model, which verifies the effectiveness and reliability of the method and reduces the complexity of landmark extraction process without losing the reference value of landmark.
-
Directory of Open Access Journals (Sweden)
Daisuke Tsuzuki
2017-07-01
Full Text Available The topographic relationships between the macroanatomical structure of the lateral cortex, including sulci and fissures, and anatomical landmarks on the external surface of the head are known to be consistent. This allows the coregistration of EEG electrodes or functional near-infrared spectroscopy over the scalp with underlying cortical regions. However, limited information is available as to whether the topographic relationships are maintained in rapidly developing infants, whose brains and heads exhibit drastic growth. We used MRIs of infants ranging in age from 3 to 22 months old, and identified 20 macroanatomical landmarks, featuring the junctions of major sulci and fissures, as well as cranial landmarks and virtually determined positions of the international 10-20 and 10-10 systems. A Procrustes analysis revealed developmental trends in changes of shape in both the cortex and head. An analysis of Euclidian distances between selected pairs of cortical landmarks at standard stereotactic coordinates showed anterior shifts of the relative positions of the premotor and parietal cortices with age. Finally, cortical landmark positions and their spatial variability were compared with 10-10 landmark positions. The results indicate that variability in the distribution of each macroanatomical landmark was much smaller than the pitch of the 10-10 landmarks. This study demonstrates that the scalp-based 10-10 system serves as a good frame of reference in infants not only for assessing the development of the macroanatomy of the lateral cortical structure, but also for functional studies of cortical development using transcranial modalities such as EEG and fNIRS.
-
Collaborative regression-based anatomical landmark detection
International Nuclear Information System (INIS)
Gao, Yaozong; Shen, Dinggang
2015-01-01
Anatomical landmark detection plays an important role in medical image analysis, e.g. for registration, segmentation and quantitative analysis. Among the various existing methods for landmark detection, regression-based methods have recently attracted much attention due to their robustness and efficiency. In these methods, landmarks are localised through voting from all image voxels, which is completely different from the classification-based methods that use voxel-wise classification to detect landmarks. Despite their robustness, the accuracy of regression-based landmark detection methods is often limited due to (1) the inclusion of uninformative image voxels in the voting procedure, and (2) the lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. (1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localise landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for informative voxels near the landmark, a spherical sampling strategy is also designed at the training stage to improve their prediction accuracy. (2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of ‘difficult-to-detect’ landmarks by using spatial guidance from ‘easy-to-detect’ landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head and neck landmarks in computed tomography images, and also dental landmarks in cone beam computed tomography images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods. (paper)
-
Landmark Agnosia: Evaluating the Definition of Landmark-based Navigation Impairment.
van der Ham, Ineke J M; Martens, Marieke A G; Claessen, Michiel H G; van den Berg, Esther
2017-06-01
Landmark agnosia is a rare type of navigation impairment, for which various definitions have been presented. From a clinical as well as theoretical perspective, consensus on the characteristics of landmark agnosia would be valuable. In the current study we review the literature concerning landmark agnosia and present a new case study. Existing literature highlights the importance of examining familiar as well as novel landmark processing and substantial variation in performance patterns of individual patients. We performed a case study with patient KS, a 53-year-old male, suffering from landmark agnosia, making use of elaborate neuropsychological screening and virtual reality-based tests of navigation ability. Our extensive examination of his impairment shows that landmark agnosia can be very narrow; in KS it is restricted to recognition of newly learned landmarks only. Also, he has no trouble recognizing familiar landmarks that are not part of a navigated route. The literature review shows that the right temporal lobe, and the right hippocampus in particular are the main lesion sites for landmark agnosia. Furthermore, our case study substantiates that this disorder can occur for both familiar and novel landmarks, and can affect novel landmarks in isolation from familiar landmarks. Moreover, it can occur in isolation from problems with processing route information. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
-
Directory of Open Access Journals (Sweden)
Yi Hou
2017-01-01
Full Text Available Efficient and robust visual localization is important for autonomous vehicles. By achieving impressive localization accuracy under conditions of significant changes, ConvNet landmark-based approach has attracted the attention of people in several research communities including autonomous vehicles. Such an approach relies heavily on the outstanding discrimination power of ConvNet features to match detected landmarks between images. However, a major challenge of this approach is how to extract discriminative ConvNet features efficiently. To address this challenging, inspired by the high efficiency of the region of interest (RoI pooling layer, we propose a Multiple RoI (MRoI pooling technique, an enhancement of RoI, and a simple yet efficient ConvNet feature extraction method. Our idea is to leverage MRoI pooling to exploit multilevel and multiresolution information from multiple convolutional layers and then fuse them to improve the discrimination capacity of the final ConvNet features. The main advantages of our method are (a high computational efficiency for real-time applications; (b GPU memory efficiency for mobile applications; and (c use of pretrained model without fine-tuning or retraining for easy implementation. Experimental results on four datasets have demonstrated not only the above advantages but also the high discriminating power of the extracted ConvNet features with state-of-the-art localization accuracy.
-
Directory of Open Access Journals (Sweden)
Yutong Liu
2012-01-01
Full Text Available Purpose. To develop a technique to automate landmark selection for point-based interpolating transformations for nonlinear medical image registration. Materials and Methods. Interpolating transformations were calculated from homologous point landmarks on the source (image to be transformed and target (reference image. Point landmarks are placed at regular intervals on contours of anatomical features, and their positions are optimized along the contour surface by a function composed of curvature similarity and displacements of the homologous landmarks. The method was evaluated in two cases (=5 each. In one, MRI was registered to histological sections; in the second, geometric distortions in EPI MRI were corrected. Normalized mutual information and target registration error were calculated to compare the registration accuracy of the automatically and manually generated landmarks. Results. Statistical analyses demonstrated significant improvement (<0.05 in registration accuracy by landmark optimization in most data sets and trends towards improvement (<0.1 in others as compared to manual landmark selection.
-
Adaptive Landmark-Based Navigation System Using Learning Techniques
DEFF Research Database (Denmark)
Zeidan, Bassel; Dasgupta, Sakyasingha; Wörgötter, Florentin
2014-01-01
The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal. In...... hexapod robots. As a result, it allows the robots to successfully learn to navigate to distal goals in complex environments.......The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal....... Inspired by this, we develop an adaptive landmark-based navigation system based on sequential reinforcement learning. In addition, correlation-based learning is also integrated into the system to improve learning performance. The proposed system has been applied to simulated simple wheeled and more complex...
-
Towards Real-Time Facial Landmark Detection in Depth Data Using Auxiliary Information
Directory of Open Access Journals (Sweden)
Connah Kendrick
2018-06-01
Full Text Available Modern facial motion capture systems employ a two-pronged approach for capturing and rendering facial motion. Visual data (2D is used for tracking the facial features and predicting facial expression, whereas Depth (3D data is used to build a series of expressions on 3D face models. An issue with modern research approaches is the use of a single data stream that provides little indication of the 3D facial structure. We compare and analyse the performance of Convolutional Neural Networks (CNN using visual, Depth and merged data to identify facial features in real-time using a Depth sensor. First, we review the facial landmarking algorithms and its datasets for Depth data. We address the limitation of the current datasets by introducing the Kinect One Expression Dataset (KOED. Then, we propose the use of CNNs for the single data stream and merged data streams for facial landmark detection. We contribute to existing work by performing a full evaluation on which streams are the most effective for the field of facial landmarking. Furthermore, we improve upon the existing work by extending neural networks to predict into 3D landmarks in real-time with additional observations on the impact of using 2D landmarks as auxiliary information. We evaluate the performance by using Mean Square Error (MSE and Mean Average Error (MAE. We observe that the single data stream predicts accurate facial landmarks on Depth data when auxiliary information is used to train the network. The codes and dataset used in this paper will be made available.
-
Directory of Open Access Journals (Sweden)
Marcel eMertes
2014-09-01
Full Text Available Bees use visual memories to find the spatial location of previously learnt food sites. Characteristic learning flights help acquiring these memories at newly discovered foraging locations where landmarks - salient objects in the vicinity of the goal location - can play an important role in guiding the animal’s homing behavior. Although behavioral experiments have shown that bees can use a variety of visual cues to distinguish objects as landmarks, the question of how landmark features are encoded by the visual system is still open. Recently, it could be shown that motion cues are sufficient to allow bees localizing their goal using landmarks that can hardly be discriminated from the background texture. Here, we tested the hypothesis that motion sensitive neurons in the bee’s visual pathway provide information about such landmarks during a learning flight and might, thus, play a role for goal localization. We tracked learning flights of free-flying bumblebees (Bombus terrestris in an arena with distinct visual landmarks, reconstructed the visual input during these flights, and replayed ego-perspective movies to tethered bumblebees while recording the activity of direction-selective wide-field neurons in their optic lobe. By comparing neuronal responses during a typical learning flight and targeted modifications of landmark properties in this movie we demonstrate that these objects are indeed represented in the bee’s visual motion pathway. We find that object-induced responses vary little with object texture, which is in agreement with behavioral evidence. These neurons thus convey information about landmark properties that are useful for view-based homing.
-
Multirobot FastSLAM Algorithm Based on Landmark Consistency Correction
Directory of Open Access Journals (Sweden)
Shi-Ming Chen
2014-01-01
Full Text Available Considering the influence of uncertain map information on multirobot SLAM problem, a multirobot FastSLAM algorithm based on landmark consistency correction is proposed. Firstly, electromagnetism-like mechanism is introduced to the resampling procedure in single-robot FastSLAM, where we assume that each sampling particle is looked at as a charged electron and attraction-repulsion mechanism in electromagnetism field is used to simulate interactive force between the particles to improve the distribution of particles. Secondly, when multiple robots observe the same landmarks, every robot is regarded as one node and Kalman-Consensus Filter is proposed to update landmark information, which further improves the accuracy of localization and mapping. Finally, the simulation results show that the algorithm is suitable and effective.
-
Landmark based localization in urban environment
Qu, Xiaozhi; Soheilian, Bahman; Paparoditis, Nicolas
2018-06-01
A landmark based localization with uncertainty analysis based on cameras and geo-referenced landmarks is presented in this paper. The system is developed to adapt different camera configurations for six degree-of-freedom pose estimation. Local bundle adjustment is applied for optimization and the geo-referenced landmarks are integrated to reduce the drift. In particular, the uncertainty analysis is taken into account. On the one hand, we estimate the uncertainties of poses to predict the precision of localization. On the other hand, uncertainty propagation is considered for matching, tracking and landmark registering. The proposed method is evaluated on both KITTI benchmark and the data acquired by a mobile mapping system. In our experiments, decimeter level accuracy can be reached.
-
Tree-based indexing for real-time ConvNet landmark-based visual place recognition
Directory of Open Access Journals (Sweden)
Yi Hou
2017-01-01
Full Text Available Recent impressive studies on using ConvNet landmarks for visual place recognition take an approach that involves three steps: (a detection of landmarks, (b description of the landmarks by ConvNet features using a convolutional neural network, and (c matching of the landmarks in the current view with those in the database views. Such an approach has been shown to achieve the state-of-the-art accuracy even under significant viewpoint and environmental changes. However, the computational burden in step (c significantly prevents this approach from being applied in practice, due to the complexity of linear search in high-dimensional space of the ConvNet features. In this article, we propose two simple and efficient search methods to tackle this issue. Both methods are built upon tree-based indexing. Given a set of ConvNet features of a query image, the first method directly searches the features’ approximate nearest neighbors in a tree structure that is constructed from ConvNet features of database images. The database images are voted on by features in the query image, according to a lookup table which maps each ConvNet feature to its corresponding database image. The database image with the highest vote is considered the solution. Our second method uses a coarse-to-fine procedure: the coarse step uses the first method to coarsely find the top-N database images, and the fine step performs a linear search in Hamming space of the hash codes of the ConvNet features to determine the best match. Experimental results demonstrate that our methods achieve real-time search performance on five data sets with different sizes and various conditions. Most notably, by achieving an average search time of 0.035 seconds/query, our second method improves the matching efficiency by the three orders of magnitude over a linear search baseline on a database with 20,688 images, with negligible loss in place recognition accuracy.
-
Zhang, Jun; Gao, Yaozong; Wang, Li; Tang, Zhen; Xia, James J.; Shen, Dinggang
2016-01-01
Objective The goal of this paper is to automatically digitize craniomaxillofacial (CMF) landmarks efficiently and accurately from cone-beam computed tomography (CBCT) images, by addressing the challenge caused by large morphological variations across patients and image artifacts of CBCT images. Methods We propose a Segmentation-guided Partially-joint Regression Forest (S-PRF) model to automatically digitize CMF landmarks. In this model, a regression voting strategy is first adopted to localize each landmark by aggregating evidences from context locations, thus potentially relieving the problem caused by image artifacts near the landmark. Second, CBCT image segmentation is utilized to remove uninformative voxels caused by morphological variations across patients. Third, a partially-joint model is further proposed to separately localize landmarks based on the coherence of landmark positions to improve the digitization reliability. In addition, we propose a fast vector quantization (VQ) method to extract high-level multi-scale statistical features to describe a voxel's appearance, which has low dimensionality, high efficiency, and is also invariant to the local inhomogeneity caused by artifacts. Results Mean digitization errors for 15 landmarks, in comparison to the ground truth, are all less than 2mm. Conclusion Our model has addressed challenges of both inter-patient morphological variations and imaging artifacts. Experiments on a CBCT dataset show that our approach achieves clinically acceptable accuracy for landmark digitalization. Significance Our automatic landmark digitization method can be used clinically to reduce the labor cost and also improve digitalization consistency. PMID:26625402
-
Tong, Yubing; Udupa, Jayaram K.; Odhner, Dewey; Bai, Peirui; Torigian, Drew A.
2017-03-01
Much has been published on finding landmarks on object surfaces in the context of shape modeling. While this is still an open problem, many of the challenges of past approaches can be overcome by removing the restriction that landmarks must be on the object surface. The virtual landmarks we propose may reside inside, on the boundary of, or outside the object and are tethered to the object. Our solution is straightforward, simple, and recursive in nature, proceeding from global features initially to local features in later levels to detect landmarks. Principal component analysis (PCA) is used as an engine to recursively subdivide the object region. The object itself may be represented in binary or fuzzy form or with gray values. The method is illustrated in 3D space (although it generalizes readily to spaces of any dimensionality) on four objects (liver, trachea and bronchi, and outer boundaries of left and right lungs along pleura) derived from 5 patient computed tomography (CT) image data sets of the thorax and abdomen. The virtual landmark identification approach seems to work well on different structures in different subjects and seems to detect landmarks that are homologously located in different samples of the same object. The approach guarantees that virtual landmarks are invariant to translation, scaling, and rotation of the object/image. Landmarking techniques are fundamental for many computer vision and image processing applications, and we are currently exploring the use virtual landmarks in automatic anatomy recognition and object analytics.
-
Finding Home: Landmark Ambiguity in Human Navigation
Directory of Open Access Journals (Sweden)
Simon Jetzschke
2017-07-01
Full Text Available Memories of places often include landmark cues, i.e., information provided by the spatial arrangement of distinct objects with respect to the target location. To study how humans combine landmark information for navigation, we conducted two experiments: To this end, participants were either provided with auditory landmarks while walking in a large sports hall or with visual landmarks while walking on a virtual-reality treadmill setup. We found that participants cannot reliably locate their home position due to ambiguities in the spatial arrangement when only one or two uniform landmarks provide cues with respect to the target. With three visual landmarks that look alike, the task is solved without ambiguity, while audio landmarks need to play three unique sounds for a similar performance. This reduction in ambiguity through integration of landmark information from 1, 2, and 3 landmarks is well modeled using a probabilistic approach based on maximum likelihood estimation. Unlike any deterministic model of human navigation (based e.g., on distance or angle information, this probabilistic model predicted both the precision and accuracy of the human homing performance. To further examine how landmark cues are integrated we introduced systematic conflicts in the visual landmark configuration between training of the home position and tests of the homing performance. The participants integrated the spatial information from each landmark near-optimally to reduce spatial variability. When the conflict becomes big, this integration breaks down and precision is sacrificed for accuracy. That is, participants return again closer to the home position, because they start ignoring the deviant third landmark. Relying on two instead of three landmarks, however, goes along with responses that are scattered over a larger area, thus leading to higher variability. To model the breakdown of integration with increasing conflict, the probabilistic model based on a
-
Neural Network Based Sensory Fusion for Landmark Detection
Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.
1997-01-01
NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.
-
Visual EKF-SLAM from Heterogeneous Landmarks.
Esparza-Jiménez, Jorge Othón; Devy, Michel; Gordillo, José L
2016-04-07
Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map when a camera moves in an unknown environment. Such a SLAM process executes two interleaved functions: the front-end detects and tracks features from images, while the back-end interprets features as landmark observations and estimates both the landmarks and the robot positions with respect to a selected reference frame. This paper describes a complete visual SLAM solution, combining both point and line landmarks on a single map. The proposed method has an impact on both the back-end and the front-end. The contributions comprehend the use of heterogeneous landmark-based EKF-SLAM (the management of a map composed of both point and line landmarks); from this perspective, the comparison between landmark parametrizations and the evaluation of how the heterogeneity improves the accuracy on the camera localization, the development of a front-end active-search process for linear landmarks integrated into SLAM and the experimentation methodology.
-
Zhao, Xi; Dellandréa, Emmanuel; Chen, Liming; Kakadiaris, Ioannis A
2011-10-01
Three-dimensional face landmarking aims at automatically localizing facial landmarks and has a wide range of applications (e.g., face recognition, face tracking, and facial expression analysis). Existing methods assume neutral facial expressions and unoccluded faces. In this paper, we propose a general learning-based framework for reliable landmark localization on 3-D facial data under challenging conditions (i.e., facial expressions and occlusions). Our approach relies on a statistical model, called 3-D statistical facial feature model, which learns both the global variations in configurational relationships between landmarks and the local variations of texture and geometry around each landmark. Based on this model, we further propose an occlusion classifier and a fitting algorithm. Results from experiments on three publicly available 3-D face databases (FRGC, BU-3-DFE, and Bosphorus) demonstrate the effectiveness of our approach, in terms of landmarking accuracy and robustness, in the presence of expressions and occlusions.
-
Visual EKF-SLAM from Heterogeneous Landmarks †
Esparza-Jiménez, Jorge Othón; Devy, Michel; Gordillo, José L.
2016-01-01
Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map when a camera moves in an unknown environment. Such a SLAM process executes two interleaved functions: the front-end detects and tracks features from images, while the back-end interprets features as landmark observations and estimates both the landmarks and the robot positions with respect to a selected reference frame. This paper describes a complete visual SLAM solution, combining both point and line landmarks on a single map. The proposed method has an impact on both the back-end and the front-end. The contributions comprehend the use of heterogeneous landmark-based EKF-SLAM (the management of a map composed of both point and line landmarks); from this perspective, the comparison between landmark parametrizations and the evaluation of how the heterogeneity improves the accuracy on the camera localization, the development of a front-end active-search process for linear landmarks integrated into SLAM and the experimentation methodology. PMID:27070602
-
Landmark-based elastic registration using approximating thin-plate splines.
Rohr, K; Stiehl, H S; Sprengel, R; Buzug, T M; Weese, J; Kuhn, M H
2001-06-01
We consider elastic image registration based on a set of corresponding anatomical point landmarks and approximating thin-plate splines. This approach is an extension of the original interpolating thin-plate spline approach and allows to take into account landmark localization errors. The extension is important for clinical applications since landmark extraction is always prone to error. Our approach is based on a minimizing functional and can cope with isotropic as well as anisotropic landmark errors. In particular, in the latter case it is possible to include different types of landmarks, e.g., unique point landmarks as well as arbitrary edge points. Also, the scheme is general with respect to the image dimension and the order of smoothness of the underlying functional. Optimal affine transformations as well as interpolating thin-plate splines are special cases of this scheme. To localize landmarks we use a semi-automatic approach which is based on three-dimensional (3-D) differential operators. Experimental results are presented for two-dimensional as well as 3-D tomographic images of the human brain.
-
DETEKSI LANDMARK CITRA WAJAH DENGAN EXTRAKSI FITUR GABOR ANALISA FUZZY
Directory of Open Access Journals (Sweden)
Resmana Lim
2003-01-01
Full Text Available This paper proposes a method that automatically finds human faces as well as its landmark points in color images based on a fuzzy analysis. The proposed approach first uses color information to detect face candidate regions and then uses a fuzzy analysis of the color, shape, symmetry and interior facial features. A deformable Gabor wavelet graph matching is used to locate the facial landmark points describing the face. The latter allows for size and orientation variation since the search for landmark points allows for affine transformations as well as local deformations of the Gabor wavelet graph. The search is performed using a genetic algorithm that is essential because it effectively searches the solution space. Results based on the proposed method are included to verify the effectiveness of the proposed approach. Abstract in Bahasa Indonesia : Paper ini mengusulkan sebuah metode deteksi wajah beserta dengan titik landmarknya pada citra berwarna menggunakan analisa fuzzy. Proses awal menggunakan informasi warna kulit untuk menseleksi calon-calon obyek lantas dilanjukan dengan analisa fuzzy terhadap warna, bentuk, simetri dan fitur/landmark wajah. Proses lokalisasi landmark wajah menggunakan Gabor wavelet graph matching dengan memaksimalkan kemiripan antara landmark wajah model dengan obyek inputan. Proses maksimalisasi kemiripan ini menggunakan algoritma genetika. Hasil-hasil percobaan ditampilkan untuk memberikan gambaran keberhasilan dari metode yang diusulkan. Kata kunci: lokalisasi landmark wajah, analisa fuzzy, graph matching, algoritma genetika, Gabor wavelet.
-
Byrne, Patrick A; Crawford, J Douglas
2010-06-01
It is not known how egocentric visual information (location of a target relative to the self) and allocentric visual information (location of a target relative to external landmarks) are integrated to form reach plans. Based on behavioral data from rodents and humans we hypothesized that the degree of stability in visual landmarks would influence the relative weighting. Furthermore, based on numerous cue-combination studies we hypothesized that the reach system would act like a maximum-likelihood estimator (MLE), where the reliability of both cues determines their relative weighting. To predict how these factors might interact we developed an MLE model that weighs egocentric and allocentric information based on their respective reliabilities, and also on an additional stability heuristic. We tested the predictions of this model in 10 human subjects by manipulating landmark stability and reliability (via variable amplitude vibration of the landmarks and variable amplitude gaze shifts) in three reach-to-touch tasks: an egocentric control (reaching without landmarks), an allocentric control (reaching relative to landmarks), and a cue-conflict task (involving a subtle landmark "shift" during the memory interval). Variability from all three experiments was used to derive parameters for the MLE model, which was then used to simulate egocentric-allocentric weighting in the cue-conflict experiment. As predicted by the model, landmark vibration--despite its lack of influence on pointing variability (and thus allocentric reliability) in the control experiment--had a strong influence on egocentric-allocentric weighting. A reduced model without the stability heuristic was unable to reproduce this effect. These results suggest heuristics for extrinsic cue stability are at least as important as reliability for determining cue weighting in memory-guided reaching.
-
Landmark Detection in Orbital Images Using Salience Histograms
Wagstaff, Kiri L.; Panetta, Julian; Schorghofer, Norbert; Greeley, Ronald; PendletonHoffer, Mary; bunte, Melissa
2010-01-01
NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.
-
Probability-Based Recognition Framework for Underwater Landmarks Using Sonar Images †.
Lee, Yeongjun; Choi, Jinwoo; Ko, Nak Yong; Choi, Hyun-Taek
2017-08-24
This paper proposes a probability-based framework for recognizing underwater landmarks using sonar images. Current recognition methods use a single image, which does not provide reliable results because of weaknesses of the sonar image such as unstable acoustic source, many speckle noises, low resolution images, single channel image, and so on. However, using consecutive sonar images, if the status-i.e., the existence and identity (or name)-of an object is continuously evaluated by a stochastic method, the result of the recognition method is available for calculating the uncertainty, and it is more suitable for various applications. Our proposed framework consists of three steps: (1) candidate selection, (2) continuity evaluation, and (3) Bayesian feature estimation. Two probability methods-particle filtering and Bayesian feature estimation-are used to repeatedly estimate the continuity and feature of objects in consecutive images. Thus, the status of the object is repeatedly predicted and updated by a stochastic method. Furthermore, we develop an artificial landmark to increase detectability by an imaging sonar, which we apply to the characteristics of acoustic waves, such as instability and reflection depending on the roughness of the reflector surface. The proposed method is verified by conducting basin experiments, and the results are presented.
-
Robust facial landmark detection based on initializing multiple poses
Directory of Open Access Journals (Sweden)
Xin Chai
2016-10-01
Full Text Available For robot systems, robust facial landmark detection is the first and critical step for face-based human identification and facial expression recognition. In recent years, the cascaded-regression-based method has achieved excellent performance in facial landmark detection. Nevertheless, it still has certain weakness, such as high sensitivity to the initialization. To address this problem, regression based on multiple initializations is established in a unified model; face shapes are then estimated independently according to these initializations. With a ranking strategy, the best estimate is selected as the final output. Moreover, a face shape model based on restricted Boltzmann machines is built as a constraint to improve the robustness of ranking. Experiments on three challenging datasets demonstrate the effectiveness of the proposed facial landmark detection method against state-of-the-art methods.
-
Landmarks selection in street map design
International Nuclear Information System (INIS)
Kao, C J
2014-01-01
In Taiwan many electrical maps present their landmarks according to the category of the feature, a designer short of knowledge about mental representation of space, can cause the map to lose its communication effects. To resolve this map design problem, in this research through long-term memory recall, navigation and observation, and short-term memory processing 111 participants were asked to select the proper landmark from study area. The results reveal that in Taiwan convenience stores are the most popular local landmark in rural and urban areas. Their commercial signs have a unique design and bright color. Contrasted to their background, this makes the convenience store a salient feature. This study also developed a rule to assess the priority of the landmarks to design them in different scale maps
-
Landmarks selection in street map design
Kao, C. J.
2014-02-01
In Taiwan many electrical maps present their landmarks according to the category of the feature, a designer short of knowledge about mental representation of space, can cause the map to lose its communication effects. To resolve this map design problem, in this research through long-term memory recall, navigation and observation, and short-term memory processing 111 participants were asked to select the proper landmark from study area. The results reveal that in Taiwan convenience stores are the most popular local landmark in rural and urban areas. Their commercial signs have a unique design and bright color. Contrasted to their background, this makes the convenience store a salient feature. This study also developed a rule to assess the priority of the landmarks to design them in different scale maps.
-
Landmark-based augmented reality system for paranasal and transnasal endoscopic surgeries.
Thoranaghatte, Ramesh; Garcia, Jaime; Caversaccio, Marco; Widmer, Daniel; Gonzalez Ballester, Miguel A; Nolte, Lutz-P; Zheng, Guoyan
2009-12-01
In this paper we present a landmark-based augmented reality (AR) endoscope system for endoscopic paranasal and transnasal surgeries along with fast and automatic calibration and registration procedures for the endoscope. Preoperatively the surgeon selects natural landmarks or can define new landmarks in CT volume. These landmarks are overlaid, after proper registration of preoperative CT to the patient, on the endoscopic video stream. The specified name of the landmark, along with selected colour and its distance from the endoscope tip, is also augmented. The endoscope optics are calibrated and registered by fast and automatic methods. Accuracy of the system is evaluated in a metallic grid and cadaver set-up. Root mean square (RMS) error of the system is 0.8 mm in a controlled laboratory set-up (metallic grid) and was 2.25 mm during cadaver studies. A novel landmark-based AR endoscope system is implemented and its accuracy is evaluated. Augmented landmarks will help the surgeon to orientate and navigate the surgical field. Studies prove the capability of the system for the proposed application. Further clinical studies are planned in near future. Copyright (c) 2009 John Wiley & Sons, Ltd.
-
Autonomous Robot Navigation based on Visual Landmarks
DEFF Research Database (Denmark)
Livatino, Salvatore
2005-01-01
The use of landmarks for robot navigation is a popular alternative to having a geometrical model of the environment through which to navigate and monitor self-localization. If the landmarks are defined as special visual structures already in the environment then we have the possibility of fully a...... automatically learn and store visual landmarks, and later recognize these landmarks from arbitrary positions and thus estimate robot position and heading.......The use of landmarks for robot navigation is a popular alternative to having a geometrical model of the environment through which to navigate and monitor self-localization. If the landmarks are defined as special visual structures already in the environment then we have the possibility of fully...... autonomous navigation and self-localization using automatically selected landmarks. The thesis investigates autonomous robot navigation and proposes a new method which benefits from the potential of the visual sensor to provide accuracy and reliability to the navigation process while relying on naturally...
-
Sekiguchi, Katsuo; Ushitani, Tomokazu; Sawa, Kosuke
2018-05-01
Landmark-based goal-searching tasks that were similar to those for pigeons (Ushitani & Jitsumori, 2011) were provided to human participants to investigate whether they could learn and use multiple sources of spatial information that redundantly indicate the position of a hidden target in both an open field (Experiment 1) and on a computer screen (Experiments 2 and 3). During the training in each experiment, participants learned to locate a target in 1 of 25 objects arranged in a 5 × 5 grid, using two differently colored, arrow-shaped (Experiments 1 and 2) or asymmetrically shaped (Experiment 3) landmarks placed adjacent to the goal and pointing to the goal location. The absolute location and directions of the landmarks varied across trials, but the constant configuration of the goal and the landmarks enabled participants to find the goal using both global configural information and local vector information (pointing to the goal by each individual landmark). On subsequent test trials, the direction was changed for one of the landmarks to conflict with the global configural information. Results of Experiment 1 indicated that participants used vector information from a single landmark but not configural information. Further examinations revealed that the use of global (metric) information was enhanced remarkably by goal searching with nonarrow-shaped landmarks on the computer monitor (Experiment 3) but much less so with arrow-shaped landmarks (Experiment 2). The General Discussion focuses on a comparison between humans in the current study and pigeons in the previous study. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
-
A statistical method for 2D facial landmarking
Dibeklioğlu, H.; Salah, A.A.; Gevers, T.
2012-01-01
Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in
-
Study of robot landmark recognition with complex background
Huang, Yuqing; Yang, Jia
2007-12-01
It's of great importance for assisting robot in path planning, position navigating and task performing by perceiving and recognising environment characteristic. To solve the problem of monocular-vision-oriented landmark recognition for mobile intelligent robot marching with complex background, a kind of nested region growing algorithm which fused with transcendental color information and based on current maximum convergence center is proposed, allowing invariance localization to changes in position, scale, rotation, jitters and weather conditions. Firstly, a novel experiment threshold based on RGB vision model is used for the first image segmentation, which allowing some objects and partial scenes with similar color to landmarks also are detected with landmarks together. Secondly, with current maximum convergence center on segmented image as each growing seed point, the above region growing algorithm accordingly starts to establish several Regions of Interest (ROI) orderly. According to shape characteristics, a quick and effectual contour analysis based on primitive element is applied in deciding whether current ROI could be reserved or deleted after each region growing, then each ROI is judged initially and positioned. When the position information as feedback is conveyed to the gray image, the whole landmarks are extracted accurately with the second segmentation on the local image that exclusive to landmark area. Finally, landmarks are recognised by Hopfield neural network. Results issued from experiments on a great number of images with both campus and urban district as background show the effectiveness of the proposed algorithm.
-
WIKIPEDIA ENTRIES AS A SOURCE OF CAR NAVIGATION LANDMARKS
Directory of Open Access Journals (Sweden)
N. Binski
2016-06-01
Full Text Available Car navigation system devices provide today with an easy and simple solution to the basic concept of reaching a destination. Although these systems usually achieve this goal, they still deliver a limited and poor sequence of instructions that do not consider the human nature of using landmarks during wayfinding. This research paper addresses the concept of enriching navigation route instructions by adding supplementary route information in the form of landmarks. We aim at using a contributed source of landmarks information, which is easy to access, available, show high update rate, and have a large scale of information. For this, Wikipedia was chosen, since it represents the world’s largest free encyclopaedia that includes information about many spatial entities. A survey and classification of available landmarks is implemented, coupled with ranking algorithms based on the entries’ categories and attributes. These are aimed at retrieving the most relevant landmark information required that are valuable for the enrichment of a specific navigation route. The paper will present this methodology, together with examples and results, showing the feasibility of using this concept and its potential of enriching navigation processes.
-
3D ultrasound-CT registration of the liver using combined landmark-intensity information
International Nuclear Information System (INIS)
Lange, Thomas; Schlag, Peter M.; Papenberg, Nils; Heldmann, Stefan; Modersitzki, Jan; Fischer, Bernd; Lamecker, Hans
2009-01-01
An important issue in computer-assisted surgery of the liver is a fast and reliable transfer of preoperative resection plans to the intraoperative situation. One problem is to match the planning data, derived from preoperative CT or MR images, with 3D ultrasound images of the liver, acquired during surgery. As the liver deforms significantly in the intraoperative situation non-rigid registration is necessary. This is a particularly challenging task because pre- and intraoperative image data stem from different modalities and ultrasound images are generally very noisy. One way to overcome these problems is to incorporate prior knowledge into the registration process. We propose a method of combining anatomical landmark information with a fast non-parametric intensity registration approach. Mathematically, this leads to a constrained optimization problem. As distance measure we use the normalized gradient field which allows for multimodal image registration. A qualitative and quantitative validation on clinical liver data sets of three different patients has been performed. We used the distance of dense corresponding points on vessel center lines for quantitative validation. The combined landmark and intensity approach improves the mean and percentage of point distances above 3 mm compared to rigid and thin-plate spline registration based only on landmarks. The proposed algorithm offers the possibility to incorporate additional a priori knowledge - in terms of few landmarks - provided by a human expert into a non-rigid registration process. (orig.)
-
FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES
Directory of Open Access Journals (Sweden)
Ratri Enggar Pawening
2016-06-01
Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.
-
Colon flattening by landmark-driven optimal quasiconformal mapping.
Zeng, Wei; Yang, Yi-Jun
2014-01-01
In virtual colonoscopy, colon conformal flattening plays an important role, which unfolds the colon wall surface to a rectangle planar image and preserves local shapes by conformal mapping, so that the cancerous polyps and other abnormalities can be easily and thoroughly recognized and visualized without missing hidden areas. In such maps, the anatomical landmarks (taeniae coli, flexures, and haustral folds) are naturally mapped to convoluted curves on 2D domain, which poses difficulty for comparing shapes from geometric feature details. Understanding the nature of landmark curves to the whole surface structure is meaningful but it remains challenging and open. In this work, we present a novel and effective colon flattening method based on quasiconformal mapping, which straightens the main anatomical landmark curves with least conformality (angle) distortion. It provides a canonical and straightforward view of the long, convoluted and folded tubular colon surface. The computation is based on the holomorphic 1-form method with landmark straightening constraints and quasiconformal optimization, and has linear time complexity due to the linearity of 1-forms in each iteration. Experiments on various colon data demonstrate the efficiency and efficacy of our algorithm and its practicability for polyp detection and findings visualization; furthermore, the result reveals the geometric characteristics of anatomical landmarks on colon surfaces.
-
77 FR 44670 - Information Collection Activities: National Historic Landmarks (NHL) Condition Survey
2012-07-30
... information regarding the condition of designated landmarks. A questionnaire will be designed and used to... the design of the questionnaire that is the subject of this request. II. Data OMB Control Number: 1024... address, phone number, email address, or other personal identifying information in your comment, you...
-
International Nuclear Information System (INIS)
Hunsche, S; Sauner, D; Maarouf, M; Hoevels, M; Luyken, K; Schulte, O; Lackner, K; Sturm, V; Treuer, H
2004-01-01
For application in magnetic resonance (MR) guided stereotactic neurosurgery, two methods for transformation of MR-image coordinates in stereotactic, frame-based coordinates exist: the direct stereotactic fiducial-based transformation method and the indirect anatomical landmark method. In contrast to direct stereotactic MR transformation, indirect transformation is based on anatomical landmark coregistration of stereotactic computerized tomography and non-stereotactic MR images. In a patient study, both transformation methods have been investigated with visual inspection and mutual information analysis. Comparison was done for our standard imaging protocol, including t2-weighted spin-echo as well as contrast enhanced t1-weighted gradient-echo imaging. For t2-weighted spin-echo imaging, both methods showed almost similar and satisfying performance with a small, but significant advantage for fiducial-based transformation. In contrast, for t1-weighted gradient-echo imaging with more geometric distortions due to field inhomogenities and gradient nonlinearity than t2-weighted spin-echo imaging, mainly caused by a reduced bandwidth per pixel, anatomical landmark transformation delivered markedly better results. Here, fiducial-based transformation yielded results which are intolerable for stereotactic neurosurgery. Mean Euclidian distances between both transformation methods were 0.96 mm for t2-weighted spin-echo and 1.67 mm for t1-weighted gradient-echo imaging. Maximum deviations were 1.72 mm and 3.06 mm, respectively
-
Energy Technology Data Exchange (ETDEWEB)
Hunsche, S [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Sauner, D [Institute for Diagnostic and Interventional Radiology, Friedrich-Schiller-University of Jena, Jena (Germany); Maarouf, M [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Hoevels, M [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Luyken, K [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Schulte, O [Department of Radiology, University of Cologne, Cologne (Germany); Lackner, K [Department of Radiology, University of Cologne, Cologne (Germany); Sturm, V [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany); Treuer, H [Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne (Germany)
2004-06-21
For application in magnetic resonance (MR) guided stereotactic neurosurgery, two methods for transformation of MR-image coordinates in stereotactic, frame-based coordinates exist: the direct stereotactic fiducial-based transformation method and the indirect anatomical landmark method. In contrast to direct stereotactic MR transformation, indirect transformation is based on anatomical landmark coregistration of stereotactic computerized tomography and non-stereotactic MR images. In a patient study, both transformation methods have been investigated with visual inspection and mutual information analysis. Comparison was done for our standard imaging protocol, including t2-weighted spin-echo as well as contrast enhanced t1-weighted gradient-echo imaging. For t2-weighted spin-echo imaging, both methods showed almost similar and satisfying performance with a small, but significant advantage for fiducial-based transformation. In contrast, for t1-weighted gradient-echo imaging with more geometric distortions due to field inhomogenities and gradient nonlinearity than t2-weighted spin-echo imaging, mainly caused by a reduced bandwidth per pixel, anatomical landmark transformation delivered markedly better results. Here, fiducial-based transformation yielded results which are intolerable for stereotactic neurosurgery. Mean Euclidian distances between both transformation methods were 0.96 mm for t2-weighted spin-echo and 1.67 mm for t1-weighted gradient-echo imaging. Maximum deviations were 1.72 mm and 3.06 mm, respectively.
-
Pappas, Marjorie L.
2003-01-01
Explains how to develop lesson plans to help students become effective researchers using electronic searching tools. Uses a unit developed for Kansas landmarks to discuss information skills, competency standards, inquiry, technology use, information literacy and process skills, finding information, and an example of a research log. (LRW)
-
Evidence for discrete landmark use by pigeons during homing.
Mora, Cordula V; Ross, Jeremy D; Gorsevski, Peter V; Chowdhury, Budhaditya; Bingman, Verner P
2012-10-01
Considerable efforts have been made to investigate how homing pigeons (Columba livia f. domestica) are able to return to their loft from distant, unfamiliar sites while the mechanisms underlying navigation in familiar territory have received less attention. With the recent advent of global positioning system (GPS) data loggers small enough to be carried by pigeons, the role of visual environmental features in guiding navigation over familiar areas is beginning to be understood, yet, surprisingly, we still know very little about whether homing pigeons can rely on discrete, visual landmarks to guide navigation. To assess a possible role of discrete, visual landmarks in navigation, homing pigeons were first trained to home from a site with four wind turbines as salient landmarks as well as from a control site without any distinctive, discrete landmark features. The GPS-recorded flight paths of the pigeons on the last training release were straighter and more similar among birds from the turbine site compared with those from the control site. The pigeons were then released from both sites following a clock-shift manipulation. Vanishing bearings from the turbine site continued to be homeward oriented as 13 of 14 pigeons returned home. By contrast, at the control site the vanishing bearings were deflected in the expected clock-shift direction and only 5 of 13 pigeons returned home. Taken together, our results offer the first strong evidence that discrete, visual landmarks are one source of spatial information homing pigeons can utilize to navigate when flying over a familiar area.
-
Shang, Jianga; Gu, Fuqiang; Hu, Xuke; Kealy, Allison
2015-01-01
The utility and adoption of indoor localization applications have been limited due to the complex nature of the physical environment combined with an increasing requirement for more robust localization performance. Existing solutions to this problem are either too expensive or too dependent on infrastructure such as Wi-Fi access points. To address this problem, we propose APFiLoc—a low cost, smartphone-based framework for indoor localization. The key idea behind this framework is to obtain landmarks within the environment and to use the augmented particle filter to fuse them with measurements from smartphone sensors and map information. A clustering method based on distance constraints is developed to detect organic landmarks in an unsupervised way, and the least square support vector machine is used to classify seed landmarks. A series of real-world experiments were conducted in complex environments including multiple floors and the results show APFiLoc can achieve 80% accuracy (phone in the hand) and around 70% accuracy (phone in the pocket) of the error less than 2 m error without the assistance of infrastructure like Wi-Fi access points. PMID:26516858
-
MRI-based anatomical landmarks for the identification of thoracic vertebral levels
International Nuclear Information System (INIS)
Connor, S.E.J.; Shah, A.; Latifoltojar, H.; Lung, P.
2013-01-01
Aim: To identify soft-tissue and bony anatomical landmarks on dedicated thoracic spine magnetic resonance imaging (MRI), and to assess their detectability, reproducibility, and accuracy in predicting specific thoracic vertebral levels. Materials and methods: One hundred dedicated thoracic MRI studies were retrospectively analysed by two radiologists independently. Ten bone and soft-tissue landmarks were localized to the adjacent vertebral level. The true numerical thoracic vertebral level was subsequently determined and recorded by cross referencing with a sagittal cervico-thoracic “counting scan”. Results: Six landmarks were defined in ≥98% cases; however, there was a low interobserver percentage agreement for the defined vertebral levels (>70% for only one landmark). The most useful landmark for defining a specific vertebral level was the most superior rib (98% detection, 95% interobserver agreement, 98% at a single vertebral level, 0.07 SD). Eight landmarks localized to a specific thoracic segment in only 16–44% of cases, with a standard deviation of >0.5 vertebral levels and with a range which was greater than four vertebral levels. Conclusion: The C2 vertebra must be identified and cross referenced to the dedicated thoracic spine MRI, as other MRI-based anatomical landmarks are unreliable in determining the correct thoracic vertebral level
-
International Nuclear Information System (INIS)
Shahidi, Shoaleh; Bahrampour, Ehsan; Soltanimehr, Elham; Zamani, Ali; Oshagh, Morteza; Moattari, Marzieh; Mehdizadeh, Alireza
2014-01-01
Two-dimensional projection radiographs have been traditionally considered the modality of choice for cephalometric analysis. To overcome the shortcomings of two-dimensional images, three-dimensional computed tomography (CT) has been used to evaluate craniofacial structures. However, manual landmark detection depends on medical expertise, and the process is time-consuming. The present study was designed to produce software capable of automated localization of craniofacial landmarks on cone beam (CB) CT images based on image registration and to evaluate its accuracy. The software was designed using MATLAB programming language. The technique was a combination of feature-based (principal axes registration) and voxel similarity-based methods for image registration. A total of 8 CBCT images were selected as our reference images for creating a head atlas. Then, 20 CBCT images were randomly selected as the test images for evaluating the method. Three experts twice located 14 landmarks in all 28 CBCT images during two examinations set 6 weeks apart. The differences in the distances of coordinates of each landmark on each image between manual and automated detection methods were calculated and reported as mean errors. The combined intraclass correlation coefficient for intraobserver reliability was 0.89 and for interobserver reliability 0.87 (95% confidence interval, 0.82 to 0.93). The mean errors of all 14 landmarks were <4 mm. Additionally, 63.57% of landmarks had a mean error of <3 mm compared with manual detection (gold standard method). The accuracy of our approach for automated localization of craniofacial landmarks, which was based on combining feature-based and voxel similarity-based methods for image registration, was acceptable. Nevertheless we recommend repetition of this study using other techniques, such as intensity-based methods
-
Automatic generation of 3D statistical shape models with optimal landmark distributions.
Heimann, T; Wolf, I; Meinzer, H-P
2007-01-01
To point out the problem of non-uniform landmark placement in statistical shape modeling, to present an improved method for generating landmarks in the 3D case and to propose an unbiased evaluation metric to determine model quality. Our approach minimizes a cost function based on the minimum description length (MDL) of the shape model to optimize landmark correspondences over the training set. In addition to the standard technique, we employ an extended remeshing method to change the landmark distribution without losing correspondences, thus ensuring a uniform distribution over all training samples. To break the dependency of the established evaluation measures generalization and specificity from the landmark distribution, we change the internal metric from landmark distance to volumetric overlap. Redistributing landmarks to an equally spaced distribution during the model construction phase improves the quality of the resulting models significantly if the shapes feature prominent bulges or other complex geometry. The distribution of landmarks on the training shapes is -- beyond the correspondence issue -- a crucial point in model construction.
-
Diffusion tensor image registration using hybrid connectivity and tensor features.
Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang
2014-07-01
Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. Copyright © 2013 Wiley Periodicals, Inc.
-
Robust 3D face landmark localization based on local coordinate coding.
Song, Mingli; Tao, Dacheng; Sun, Shengpeng; Chen, Chun; Maybank, Stephen J
2014-12-01
In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists of two stages. In the first stage, we perform nose detection, relying on the fact that the nose shape is usually invariant under the variations in the pose, expression, and resolution. Then, we use the iterative closest points algorithm to find a 3D affine transformation that aligns the input face to a reference face. In the second stage, we perform resampling to build correspondences between the input 3D face and the training faces. Then, an LCC-based localization algorithm is proposed to obtain the positions of the landmarks in the input face. Experimental results show that the proposed method is comparable to state of the art methods in terms of its robustness, flexibility, and accuracy.
-
Enhancing SAT Based Planning with Landmark Knowledge
Elffers, J.; Konijnenberg, D.; Walraven, E.M.P.; Spaan, M.T.J.
2013-01-01
Several approaches exist to solve Artificial Intelligence planning problems, but little attention has been given to the combination of using landmark knowledge and satisfiability (SAT). Landmark knowledge has been exploited successfully in the heuristics of classical planning. Recently it was also
-
Semantic data association for planar features in outdoor 6D-SLAM using lidar
Ulas, C.; Temeltas, H.
2013-05-01
Simultaneous Localization and Mapping (SLAM) is a fundamental problem of the autonomous systems in GPS (Global Navigation System) denied environments. The traditional probabilistic SLAM methods uses point features as landmarks and hold all the feature positions in their state vector in addition to the robot pose. The bottleneck of the point-feature based SLAM methods is the data association problem, which are mostly based on a statistical measure. The data association performance is very critical for a robust SLAM method since all the filtering strategies are applied after a known correspondence. For point-features, two different but very close landmarks in the same scene might be confused while giving the correspondence decision when their positions and error covariance matrix are solely taking into account. Instead of using the point features, planar features can be considered as an alternative landmark model in the SLAM problem to be able to provide a more consistent data association. Planes contain rich information for the solution of the data association problem and can be distinguished easily with respect to point features. In addition, planar maps are very compact since an environment has only very limited number of planar structures. The planar features does not have to be large structures like building wall or roofs; the small plane segments can also be used as landmarks like billboards, traffic posts and some part of the bridges in urban areas. In this paper, a probabilistic plane-feature extraction method from 3DLiDAR data and the data association based on the extracted semantic information of the planar features is introduced. The experimental results show that the semantic data association provides very satisfactory result in outdoor 6D-SLAM.
-
Using Local Symmetry for Landmark Selection
Kootstra, Gert; de Jong, Sjoerd; Schomaker, Lambert R. B.; Fritz, M; Schiele, B; Piater, JH
2009-01-01
Most visual Simultaneous Localization And Mapping (SLAM) methods use interest points as landmarks in their maps of the environment. Often the interest points are detected using contrast features, for instance those of the Scale Invariant Feature Transform (SIFT). The SIFT interest points, however,
-
Uav Visual Autolocalizaton Based on Automatic Landmark Recognition
Silva Filho, P.; Shiguemori, E. H.; Saotome, O.
2017-08-01
Deploying an autonomous unmanned aerial vehicle in GPS-denied areas is a highly discussed problem in the scientific community. There are several approaches being developed, but the main strategies yet considered are computer vision based navigation systems. This work presents a new real-time computer-vision position estimator for UAV navigation. The estimator uses images captured during flight to recognize specific, well-known, landmarks in order to estimate the latitude and longitude of the aircraft. The method was tested in a simulated environment, using a dataset of real aerial images obtained in previous flights, with synchronized images, GPS and IMU data. The estimated position in each landmark recognition was compatible with the GPS data, stating that the developed method can be used as an alternative navigation system.
-
36 CFR 62.5 - Natural landmark criteria.
2010-07-01
... be characteristic of a given natural region. Such features include terrestrial and aquatic ecosystems... feature is so large as to be impracticable for natural landmark consideration (e.g., a mountain range...: Criterion Description Example Diversity In addition to its primary natural feature, area contains high...
-
UAV VISUAL AUTOLOCALIZATON BASED ON AUTOMATIC LANDMARK RECOGNITION
Directory of Open Access Journals (Sweden)
P. Silva Filho
2017-08-01
Full Text Available Deploying an autonomous unmanned aerial vehicle in GPS-denied areas is a highly discussed problem in the scientific community. There are several approaches being developed, but the main strategies yet considered are computer vision based navigation systems. This work presents a new real-time computer-vision position estimator for UAV navigation. The estimator uses images captured during flight to recognize specific, well-known, landmarks in order to estimate the latitude and longitude of the aircraft. The method was tested in a simulated environment, using a dataset of real aerial images obtained in previous flights, with synchronized images, GPS and IMU data. The estimated position in each landmark recognition was compatible with the GPS data, stating that the developed method can be used as an alternative navigation system.
-
One-shot 3D scanning by combining sparse landmarks with dense gradient information
Di Martino, Matías; Flores, Jorge; Ferrari, José A.
2018-06-01
Scene understanding is one of the most challenging and popular problems in the field of robotics and computer vision and the estimation of 3D information is at the core of most of these applications. In order to retrieve the 3D structure of a test surface we propose a single shot approach that combines dense gradient information with sparse absolute measurements. To that end, we designed a colored pattern that codes fine horizontal and vertical fringes, with sparse corners landmarks. By measuring the deformation (bending) of horizontal and vertical fringes, we are able to estimate surface local variations (i.e. its gradient field). Then corner sparse landmarks are detected and matched to infer spare absolute information about the test surface height. Local gradient information is combined with the sparse absolute values which work as anchors to guide the integration process. We show that this can be mathematically done in a very compact and intuitive way by properly defining a Poisson-like partial differential equation. Then we address in detail how the problem can be formulated in a discrete domain and how it can be practically solved by straight forward linear numerical solvers. Finally, validation experiment are presented.
-
Influence of Landmarks on Wayfinding and Brain Connectivity in Immersive Virtual Reality Environment
Directory of Open Access Journals (Sweden)
Greeshma Sharma
2017-07-01
Full Text Available Spatial navigation is influenced by landmarks, which are prominent visual features in the environment. Although previous research has focused on finding advantages of landmarks on wayfinding via experimentation; however, less attention has been given to identifying the key attributes of landmarks that facilitate wayfinding, including the study of neural correlates (involving electroencephalogram, EEG analyses. In this paper, we combine behavioral measures, virtual environment, and EEG signal-processing to provide a holistic investigation about the influence of landmarks on performance during navigation in a maze-like environment. In an experiment, participants were randomly divided into two conditions, Landmark-enriched (LM+; N = 17 and Landmark-devoid (LM-; N = 18, and asked to navigate from an initial location to a goal location in a maze. In the LM+ condition, there were landmarks placed at certain locations, which participants could use for wayfinding in the maze. However, in the LM- condition, such landmarks were not present. Beyond behavioral analyses of data, analyses were carried out of the EEG data collected using a 64-channel device. Results revealed that participants took less time and committed fewer errors in navigating the maze in the LM+ condition compared to the LM- condition. EEG analyses of the data revealed that the left-hemispheric activation was more prominent in the LM+ condition compared to the LM- condition. The event-related desynchronization/synchronization (ERD/ERS of the theta frequency band, revealed activation in the left posterior inferior and superior regions in the LM+ condition compared to the LM- condition, suggesting an occurrence of an object-location binding in the LM+ condition along with spatial transformation between representations. Moreover, directed transfer function method, which measures information flow between two regions, showed a higher number of active channels in the LM- condition compared to
-
An Efficient Ceiling-view SLAM Using Relational Constraints Between Landmarks
Directory of Open Access Journals (Sweden)
Hyukdoo Choi
2014-01-01
Full Text Available In this paper, we present a new indoor 'simultaneous localization and mapping‘ (SLAM technique based on an upward-looking ceiling camera. Adapted from our previous work [17], the proposed method employs sparsely-distributed line and point landmarks in an indoor environment to aid with data association and reduce extended Kalman filter computation as compared with earlier techniques. Further, the proposed method exploits geometric relationships between the two types of landmarks to provide added information about the environment. This geometric information is measured with an upward-looking ceiling camera and is used as a constraint in Kalman filtering. The performance of the proposed ceiling-view (CV SLAM is demonstrated through simulations and experiments. The proposed method performs localization and mapping more accurately than those methods that use the two types of landmarks without taking into account their relative geometries.
-
Landmark matching based retinal image alignment by enforcing sparsity in correspondence matrix.
Zheng, Yuanjie; Daniel, Ebenezer; Hunter, Allan A; Xiao, Rui; Gao, Jianbin; Li, Hongsheng; Maguire, Maureen G; Brainard, David H; Gee, James C
2014-08-01
Retinal image alignment is fundamental to many applications in diagnosis of eye diseases. In this paper, we address the problem of landmark matching based retinal image alignment. We propose a novel landmark matching formulation by enforcing sparsity in the correspondence matrix and offer its solutions based on linear programming. The proposed formulation not only enables a joint estimation of the landmark correspondences and a predefined transformation model but also combines the benefits of the softassign strategy (Chui and Rangarajan, 2003) and the combinatorial optimization of linear programming. We also introduced a set of reinforced self-similarities descriptors which can better characterize local photometric and geometric properties of the retinal image. Theoretical analysis and experimental results with both fundus color images and angiogram images show the superior performances of our algorithms to several state-of-the-art techniques. Copyright © 2013 Elsevier B.V. All rights reserved.
-
The Role of Emotional Landmarks on Topographical Memory.
Palmiero, Massimiliano; Piccardi, Laura
2017-01-01
The investigation of the role of emotional landmarks on human navigation has been almost totally neglected in psychological research. Therefore, the extent to which positive and negative emotional landmarks affect topographical memory as compared to neutral emotional landmark was explored. Positive, negative and neutral affect-laden images were selected as landmarks from the International Affective Picture System (IAPS) Inventory. The Walking Corsi test (WalCT) was used in order to test the landmark-based topographical memory. Participants were instructed to learn and retain an eight-square path encompassing positive, negative or neutral emotional landmarks. Both egocentric and allocentric frames of references were considered. Egocentric representation encompasses the object's relation to the self and it is generated from sensory data. Allocentric representation expresses a location with respect to an external frame regardless of the self and it is the basis for long-term storage of complex layouts. In particular, three measures of egocentric and allocentric topographical memory were taken into account: (1) the ability to learn the path; (2) the ability to recall by walking the path five minutes later; (3) the ability to reproduce the path on the outline of the WalCT. Results showed that both positive and negative emotional landmarks equally enhanced the learning of the path as compared to neutral emotional landmarks. In addition, positive emotional landmarks improved the reproduction of the path on the map as compared to negative and neutral emotional landmarks. These results generally show that emotional landmarks enhance egocentric-based topographical memory, whereas positive emotional landmarks seem to be more effective for allocentric-based topographical memory.
-
The Role of Emotional Landmarks on Topographical Memory
Directory of Open Access Journals (Sweden)
Massimiliano Palmiero
2017-05-01
Full Text Available The investigation of the role of emotional landmarks on human navigation has been almost totally neglected in psychological research. Therefore, the extent to which positive and negative emotional landmarks affect topographical memory as compared to neutral emotional landmark was explored. Positive, negative and neutral affect-laden images were selected as landmarks from the International Affective Picture System (IAPS Inventory. The Walking Corsi test (WalCT was used in order to test the landmark-based topographical memory. Participants were instructed to learn and retain an eight-square path encompassing positive, negative or neutral emotional landmarks. Both egocentric and allocentric frames of references were considered. Egocentric representation encompasses the object’s relation to the self and it is generated from sensory data. Allocentric representation expresses a location with respect to an external frame regardless of the self and it is the basis for long-term storage of complex layouts. In particular, three measures of egocentric and allocentric topographical memory were taken into account: (1 the ability to learn the path; (2 the ability to recall by walking the path five minutes later; (3 the ability to reproduce the path on the outline of the WalCT. Results showed that both positive and negative emotional landmarks equally enhanced the learning of the path as compared to neutral emotional landmarks. In addition, positive emotional landmarks improved the reproduction of the path on the map as compared to negative and neutral emotional landmarks. These results generally show that emotional landmarks enhance egocentric-based topographical memory, whereas positive emotional landmarks seem to be more effective for allocentric-based topographical memory.
-
A Feature Subset Selection Method Based On High-Dimensional Mutual Information
Directory of Open Access Journals (Sweden)
Chee Keong Kwoh
2011-04-01
Full Text Available Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y , then X is a Markov Blanket of Y . We show that in some cases, it is infeasible to approximate the high-dimensional mutual information with algebraic combinations of pairwise mutual information in any forms. In addition, the exhaustive searches of all combinations of features are prerequisite for finding the optimal feature subsets for classifying these kinds of data sets. We show that our approach outperforms existing filter feature subset selection methods for most of the 24 selected benchmark data sets.
-
Quantification of organ motion based on an adaptive image-based scale invariant feature method
Energy Technology Data Exchange (ETDEWEB)
Paganelli, Chiara [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, piazza L. Da Vinci 32, Milano 20133 (Italy); Peroni, Marta [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, piazza L. Da Vinci 32, Milano 20133, Italy and Paul Scherrer Institut, Zentrum für Protonentherapie, WMSA/C15, CH-5232 Villigen PSI (Italy); Baroni, Guido; Riboldi, Marco [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, piazza L. Da Vinci 32, Milano 20133, Italy and Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, strada Campeggi 53, Pavia 27100 (Italy)
2013-11-15
Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT
-
Map generation in unknown environments by AUKF-SLAM using line segment-type and point-type landmarks
Nishihta, Sho; Maeyama, Shoichi; Watanebe, Keigo
2018-02-01
Recently, autonomous mobile robots that collect information at disaster sites are being developed. Since it is difficult to obtain maps in advance in disaster sites, the robots being capable of autonomous movement under unknown environments are required. For this objective, the robots have to build maps, as well as the estimation of self-location. This is called a SLAM problem. In particular, AUKF-SLAM which uses corners in the environment as point-type landmarks has been developed as a solution method so far. However, when the robots move in an environment like a corridor consisting of few point-type features, the accuracy of self-location estimated by the landmark is decreased and it causes some distortions in the map. In this research, we propose AUKF-SLAM which uses walls in the environment as a line segment-type landmark. We demonstrate that the robot can generate maps in unknown environment by AUKF-SLAM, using line segment-type and point-type landmarks.
-
An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition
Li, Huibin
2015-07-29
We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.
-
An Efficient Multimodal 2D + 3D Feature-based Approach to Automatic Facial Expression Recognition
Li, Huibin; Ding, Huaxiong; Huang, Di; Wang, Yunhong; Zhao, Xi; Morvan, Jean-Marie; Chen, Liming
2015-01-01
We present a fully automatic multimodal 2D + 3D feature-based facial expression recognition approach and demonstrate its performance on the BU-3DFE database. Our approach combines multi-order gradient-based local texture and shape descriptors in order to achieve efficiency and robustness. First, a large set of fiducial facial landmarks of 2D face images along with their 3D face scans are localized using a novel algorithm namely incremental Parallel Cascade of Linear Regression (iPar-CLR). Then, a novel Histogram of Second Order Gradients (HSOG) based local image descriptor in conjunction with the widely used first-order gradient based SIFT descriptor are used to describe the local texture around each 2D landmark. Similarly, the local geometry around each 3D landmark is described by two novel local shape descriptors constructed using the first-order and the second-order surface differential geometry quantities, i.e., Histogram of mesh Gradients (meshHOG) and Histogram of mesh Shape index (curvature quantization, meshHOS). Finally, the Support Vector Machine (SVM) based recognition results of all 2D and 3D descriptors are fused at both feature-level and score-level to further improve the accuracy. Comprehensive experimental results demonstrate that there exist impressive complementary characteristics between the 2D and 3D descriptors. We use the BU-3DFE benchmark to compare our approach to the state-of-the-art ones. Our multimodal feature-based approach outperforms the others by achieving an average recognition accuracy of 86.32%. Moreover, a good generalization ability is shown on the Bosphorus database.
-
Visual cues for the retrieval of landmark memories by navigating wood ants.
Harris, Robert A; Graham, Paul; Collett, Thomas S
2007-01-23
Even on short routes, ants can be guided by multiple visual memories. We investigate here the cues controlling memory retrieval as wood ants approach a one- or two-edged landmark to collect sucrose at a point along its base. In such tasks, ants store the desired retinal position of landmark edges at several points along their route. They guide subsequent trips by retrieving the appropriate memory and moving to bring the edges in the scene toward the stored positions. The apparent width of the landmark turns out to be a powerful cue for retrieving the desired retinal position of a landmark edge. Two other potential cues, the landmark's apparent height and the distance that the ant walks, have little effect on memory retrieval. A simple model encapsulates these conclusions and reproduces the ants' routes in several conditions. According to this model, the ant stores a look-up table. Each entry contains the apparent width of the landmark and the desired retinal position of vertical edges. The currently perceived width provides an index for retrieving the associated stored edge positions. The model accounts for the population behavior of ants and the idiosyncratic training routes of individual ants. Our results imply binding between the edge of a shape and its width and, further, imply that assessing the width of a shape does not depend on the presence of any particular local feature, such as a landmark edge. This property makes the ant's retrieval and guidance system relatively robust to edge occlusions.
-
Using local symmetry for landmark selection
Kootstra, Geert; de Jong, Sjoerd; Schomaker, Lambert R. B.
2009-01-01
Most visual Simultaneous Localization And Mapping (SLAM) methods use interest points as landmarks in their maps of the environment. Often the interest points are detected using contrast features, for instance those of the Scale Invariant Feature Transform (SIFT). The SIFT interest points, however, have problems with stability, and noise robustness. Taking our inspiration from human vision, we therefore propose the use of local symmetry to select interest points. Our method, the MUlti-scale Sy...
-
Lorenz, Cristian; Hansis, Eberhard; Weese, Jürgen; Carolus, Heike
2016-03-01
Computed tomography is the modality of choice for poly-trauma patients to assess rapidly skeletal and vascular integrity of the whole body. Often several scans with and without contrast medium or with different spatial resolution are acquired. Efficient reading of the resulting extensive set of image data is vital, since it is often time critical to initiate the necessary therapeutic actions. A set of automatically found landmarks can facilitate navigation in the data and enables anatomy oriented viewing. Following this intention, we selected a comprehensive set of 17 skeletal and 5 aortic landmarks. Landmark localization models for the Discriminative Generalized Hough Transform (DGHT) were automatically created based on a set of about 20 training images with ground truth landmark positions. A hierarchical setup with 4 resolution levels was used. Localization results were evaluated on a separate test set, consisting of 50 to 128 images (depending on the landmark) with available ground truth landmark locations. The image data covers a large amount of variability caused by differences of field-of-view, resolution, contrast agent, patient gender and pathologies. The median localization error for the set of aortic landmarks was 14.4 mm and for the set of skeleton landmarks 5.5 mm. Median localization errors for individual landmarks ranged from 3.0 mm to 31.0 mm. The runtime performance for the whole landmark set is about 5s on a typical PC.
-
Kelly, Debbie M; Bischof, Walter F
2008-10-01
We investigated how human adults orient in enclosed virtual environments, when discrete landmark information is not available and participants have to rely on geometric and featural information on the environmental surfaces. In contrast to earlier studies, where, for women, the featural information from discrete landmarks overshadowed the encoding of the geometric information, Experiment 1 showed that when featural information is conjoined with the environmental surfaces, men and women encoded both types of information. Experiment 2 showed that, although both types of information are encoded, performance in locating a goal position is better if it is close to a geometrically or featurally distinct location. Furthermore, although features are relied upon more strongly than geometry, initial experience with an environment influences the relative weighting of featural and geometric cues. Taken together, these results show that human adults use a flexible strategy for encoding spatial information.
-
DEFF Research Database (Denmark)
Beatty, Erin L.; Muller-Gass, Alexandra; Wojtarowicz, Dorothy
2018-01-01
on their ability to distinguish previously studied 'old' maps from completely unfamiliar 'new' maps under conditions of high and low working memory load in the functional MRI scanner. Viewing old versus new maps was associated with relatively greater activation in a distributed set of regions including bilateral...... inferior temporal gyrus - an important region for recognizing visual objects. Critically, whereas the performance of participants who had followed a route-based strategy dropped to chance level under high working memory load, participants who had followed a landmark-based strategy performed at above chance...... levels under both high and low working memory load - reflected by relatively greater activation in the left inferior parietal lobule (i.e. rostral part of the supramarginal gyrus known as area PFt). Our findings suggest that landmark-based learning may buffer against the effects of working memory load...
-
Desert ants learn vibration and magnetic landmarks.
Directory of Open Access Journals (Sweden)
Cornelia Buehlmann
Full Text Available The desert ants Cataglyphis navigate not only by path integration but also by using visual and olfactory landmarks to pinpoint the nest entrance. Here we show that Cataglyphis noda can additionally use magnetic and vibrational landmarks as nest-defining cues. The magnetic field may typically provide directional rather than positional information, and vibrational signals so far have been shown to be involved in social behavior. Thus it remains questionable if magnetic and vibration landmarks are usually provided by the ants' habitat as nest-defining cues. However, our results point to the flexibility of the ants' navigational system, which even makes use of cues that are probably most often sensed in a different context.
-
Encoding and retrieval of landmark-related spatial cues during navigation: an fMRI study.
Wegman, Joost; Tyborowska, Anna; Janzen, Gabriele
2014-07-01
To successfully navigate, humans can use different cues from their surroundings. Learning locations in an environment can be supported by parallel subsystems in the hippocampus and the striatum. We used fMRI to look at differences in the use of object-related spatial cues while 47 participants actively navigated in an open-field virtual environment. In each trial, participants navigated toward a target object. During encoding, three positional cues (columns) with directional cues (shadows) were available. During retrieval, the removed target had to be replaced while either two objects without shadows (objects trial) or one object with a shadow (shadow trial) were available. Participants were informed in blocks about which type of retrieval trial was most likely to occur, thereby modulating expectations of having to rely on a single landmark or on a configuration of landmarks. How the spatial learning systems in the hippocampus and caudate nucleus were involved in these landmark-based encoding and retrieval processes were investigated. Landmark configurations can create a geometry similar to boundaries in an environment. It was found that the hippocampus was involved in encoding when relying on configurations of landmarks, whereas the caudate nucleus was involved in encoding when relying on single landmarks. This might suggest that the observed hippocampal activation for configurations of objects is linked to a spatial representation observed with environmental boundaries. Retrieval based on configurations of landmarks activated regions associated with the spatial updation of object locations for reorientation. When only a single landmark was available during retrieval, regions associated with updating the location of oneself were activated. There was also evidence that good between-participant performance was predicted by right hippocampal activation. This study therefore sheds light on how the brain deals with changing demands on spatial processing related purely
-
Putting emotions in routes: the influence of emotionally laden landmarks on spatial memory.
Ruotolo, F; Claessen, M H G; van der Ham, I J M
2018-04-16
The aim of this study was to assess how people memorize spatial information of emotionally laden landmarks along a route and if the emotional value of the landmarks affects the way metric and configurational properties of the route itself are represented. Three groups of participants were asked to watch a movie of a virtual walk along a route. The route could contain positive, negative, or neutral landmarks. Afterwards, participants were asked to: (a) recognize the landmarks; (b) imagine to walk distances between landmarks; (c) indicate the position of the landmarks along the route; (d) judge the length of the route; (e) draw the route. Results showed that participants who watched the route with positive landmarks were more accurate in locating the landmarks along the route and drawing the route. On the other hand, participants in the negative condition judged the route as longer than participants in the other two conditions and were less accurate in mentally reproducing distances between landmarks. The data will be interpreted in the light of the "feelings-as-information theory" by Schwarz (2010) and the most recent evidence about the effect of emotions on spatial memory. In brief, the evidence collected in this study supports the idea that spatial cognition emerges from the interaction between an organism and contextual characteristics.
-
Automated human skull landmarking with 2D Gabor wavelets
de Jong, Markus A.; Gül, Atilla; de Gijt, Jan Pieter; Koudstaal, Maarten J.; Kayser, Manfred; Wolvius, Eppo B.; Böhringer, Stefan
2018-05-01
Landmarking of CT scans is an important step in the alignment of skulls that is key in surgery planning, pre-/post-surgery comparisons, and morphometric studies. We present a novel method for automatically locating anatomical landmarks on the surface of cone beam CT-based image models of human skulls using 2D Gabor wavelets and ensemble learning. The algorithm is validated via human inter- and intra-rater comparisons on a set of 39 scans and a skull superimposition experiment with an established surgery planning software (Maxilim). Automatic landmarking results in an accuracy of 1–2 mm for a subset of landmarks around the nose area as compared to a gold standard derived from human raters. These landmarks are located in eye sockets and lower jaw, which is competitive with or surpasses inter-rater variability. The well-performing landmark subsets allow for the automation of skull superimposition in clinical applications. Our approach delivers accurate results, has modest training requirements (training set size of 30–40 items) and is generic, so that landmark sets can be easily expanded or modified to accommodate shifting landmark interests, which are important requirements for the landmarking of larger cohorts.
-
Navigating Deep Time: Landmarks for Time from the Big Bang to the Present
Delgado, Cesar
2013-01-01
People make sense of the world by comparing and relating new information to their existing landmarks. Each individual may have different landmarks, developed through idiosyncratic experiences. Identifying specific events that constitute landmarks for a group of learners may help instructors in gauging students' prior knowledge and in planning…
-
Directory of Open Access Journals (Sweden)
Rasha M. Hassan
2017-10-01
Full Text Available Background: The use of bilateral superficial cervical plexus block (BSCPB to provide analgesia for thyroid operations remains debatable. This study was done to assess the analgesic efficacy and safety of ultrasound (US guided or landmark-based BSCPB, performed under general anesthesia, compared to systemic narcotics in thyroid surgery. Patients and methods: A total of 69 patients ASA I and II scheduled for thyroid surgery were randomly assigned into three groups (23 patients each: Group (US received US guided BSCPB. Group (LM received landmark-based BSCPB. In both groups, the block was performed under general anesthesia and before surgery using 0.5% bupivacaine 12 ml on each side. Group (C who didn’t receive any block. We measured intra-operative hemodynamics and fentanyl requirements. We also measured postoperative analgesia within 24 h of surgery as regard: pethidine consumption, visual analogue scale (VAS pain scores and time to first rescue analgesic demand. Postoperative nausea and vomiting (PONV and other adverse events were noted as well. Results: There was a significant reduction in systolic blood pressure (SBP and heart rate (HR in groups US and LM compared with group C. Intra-operative fentanyl requirements were significantly increased in group C compared to groups US and LM. Time to first analgesic request was significantly longer in groups US and LM than in group C. Postoperative pethidine consumption and VAS scores, measured during the first postoperative day, were significantly higher in group C than groups US and LM. No significant difference was noted between the three groups regarding PONV. No other adverse events were recorded. No significant differences were noted between groups US and LM. Conclusion: BSCPB (US guided or landmark-based, performed under general anesthesia, effectively decreased peri-operative analgesic requirements in thyroid operations. However, there was no significant difference in analgesic efficacy or
-
Lambrey, Simon; Berthoz, Alain
2007-09-01
Numerous data in the literature provide evidence for gender differences in spatial orientation. In particular, it has been suggested that spatial representations of large-scale environments are more accurate in terms of metric information in men than in women but are richer in landmark information in women than in men. One explanatory hypothesis is that men and women differ in terms of navigational processes they used in daily life. The present study investigated this hypothesis by distinguishing two navigational processes: spatial updating by self-motion and landmark-based orientation. Subjects were asked to perform a pointing task in three experimental conditions, which differed in terms of reliability of the external landmarks that could be used. Two groups of subjects were distinguished, a mobile group and an immobile group, in which spatial updating of environmental locations did not have the same degree of importance for the correct performance of the pointing task. We found that men readily relied on an internal egocentric representation of where landmarks were expected to be in order to perform the pointing task, a representation that could be updated during self-motion (spatial updating). In contrast, women seemed to take their bearings more readily on the basis of the stable landmarks of the external world. We suggest that this gender difference in spatial orientation is not due to differences in information processing abilities but rather due to the differences in higher level strategies.
-
Endo, Yoichiro; Balloch, Jonathan C.; Grushin, Alexander; Lee, Mun Wai; Handelman, David
2016-05-01
Control of current tactical unmanned ground vehicles (UGVs) is typically accomplished through two alternative modes of operation, namely, low-level manual control using joysticks and high-level planning-based autonomous control. Each mode has its own merits as well as inherent mission-critical disadvantages. Low-level joystick control is vulnerable to communication delay and degradation, and high-level navigation often depends on uninterrupted GPS signals and/or energy-emissive (non-stealth) range sensors such as LIDAR for localization and mapping. To address these problems, we have developed a mid-level control technique where the operator semi-autonomously drives the robot relative to visible landmarks that are commonly recognizable by both humans and machines such as closed contours and structured lines. Our novel solution relies solely on optical and non-optical passive sensors and can be operated under GPS-denied, communication-degraded environments. To control the robot using these landmarks, we developed an interactive graphical user interface (GUI) that allows the operator to select landmarks in the robot's view and direct the robot relative to one or more of the landmarks. The integrated UGV control system was evaluated based on its ability to robustly navigate through indoor environments. The system was successfully field tested with QinetiQ North America's TALON UGV and Tactical Robot Controller (TRC), a ruggedized operator control unit (OCU). We found that the proposed system is indeed robust against communication delay and degradation, and provides the operator with steady and reliable control of the UGV in realistic tactical scenarios.
-
Reorienting with terrain slope and landmarks.
Nardi, Daniele; Newcombe, Nora S; Shipley, Thomas F
2013-02-01
Orientation (or reorientation) is the first step in navigation, because establishing a spatial frame of reference is essential for a sense of location and heading direction. Recent research on nonhuman animals has revealed that the vertical component of an environment provides an important source of spatial information, in both terrestrial and aquatic settings. Nonetheless, humans show large individual and sex differences in the ability to use terrain slope for reorientation. To understand why some participants--mainly women--exhibit a difficulty with slope, we tested reorientation in a richer environment than had been used previously, including both a tilted floor and a set of distinct objects that could be used as landmarks. This environment allowed for the use of two different strategies for solving the task, one based on directional cues (slope gradient) and one based on positional cues (landmarks). Overall, rather than using both cues, participants tended to focus on just one. Although men and women did not differ significantly in their encoding of or reliance on the two strategies, men showed greater confidence in solving the reorientation task. These facts suggest that one possible cause of the female difficulty with slope might be a generally lower spatial confidence during reorientation.
-
Dispersion assessment in the location of facial landmarks on photographs.
Campomanes-Álvarez, B R; Ibáñez, O; Navarro, F; Alemán, I; Cordón, O; Damas, S
2015-01-01
The morphological assessment of facial features using photographs has played an important role in forensic anthropology. The analysis of anthropometric landmarks for determining facial dimensions and angles has been considered in diverse forensic areas. Hence, the quantification of the error associated to the location of facial landmarks seems to be necessary when photographs become a key element of the forensic procedure. In this work, we statistically evaluate the inter- and intra-observer dispersions related to the facial landmark identification on photographs. In the inter-observer experiment, a set of 18 facial landmarks was provided to 39 operators. They were requested to mark only those that they could precisely place on 10 photographs with different poses (frontal, oblique, and lateral views). The frequency of landmark location was studied together with their dispersion. Regarding the intra-observer evaluation, three participants identified 13 facial points on five photographs classified in the frontal and oblique views. Each landmark location was repeated five times at intervals of at least 24 h. The frequency results reveal that glabella, nasion, subnasale, labiale superius, and pogonion obtained the highest location frequency in the three image categories. On the contrary, the lowest rate corresponds to labiale inferius and menton. Meanwhile, zygia, gonia, and gnathion were significantly more difficult to locate than other facial landmarks. They produced a significant effect on the dispersion depending on the pose of the image where they were placed, regardless of the type of observer that positioned them. In particular, zygia and gonia presented a statistically greater variation in the three image poses, while the location of gnathion is less precise in oblique view photographs. Hence, our findings suggest that the latter landmarks tend to be highly variable when determining their exact position.
-
DeCesare, A; Secanell, M; Lagravère, M O; Carey, J
2013-01-01
The purpose of this study is to minimize errors that occur when using a four vs six landmark superimpositioning method in the cranial base to define the co-ordinate system. Cone beam CT volumetric data from ten patients were used for this study. Co-ordinate system transformations were performed. A co-ordinate system was constructed using two planes defined by four anatomical landmarks located by an orthodontist. A second co-ordinate system was constructed using four anatomical landmarks that are corrected using a numerical optimization algorithm for any landmark location operator error using information from six landmarks. The optimization algorithm minimizes the relative distance and angle between the known fixed points in the two images to find the correction. Measurement errors and co-ordinates in all axes were obtained for each co-ordinate system. Significant improvement is observed after using the landmark correction algorithm to position the final co-ordinate system. The errors found in a previous study are significantly reduced. Errors found were between 1 mm and 2 mm. When analysing real patient data, it was found that the 6-point correction algorithm reduced errors between images and increased intrapoint reliability. A novel method of optimizing the overlay of three-dimensional images using a 6-point correction algorithm was introduced and examined. This method demonstrated greater reliability and reproducibility than the previous 4-point correction algorithm.
-
Peng, Yahui; Jiang, Yulei; Soylu, Fatma N.; Tomek, Mark; Sensakovic, William; Oto, Aytekin
2012-02-01
Quantitative analysis of multi-parametric magnetic resonance (MR) images of the prostate, including T2-weighted (T2w) and diffusion-weighted (DW) images, requires accurate image registration. We compared two registration methods between T2w and DW images. We collected pre-operative MR images of 124 prostate cancer patients (68 patients scanned with a GE scanner and 56 with Philips scanners). A landmark-based rigid registration was done based on six prostate landmarks in both T2w and DW images identified by a radiologist. Independently, a researcher manually registered the same images. A radiologist visually evaluated the registration results by using a 5-point ordinal scale of 1 (worst) to 5 (best). The Wilcoxon signed-rank test was used to determine whether the radiologist's ratings of the results of the two registration methods were significantly different. Results demonstrated that both methods were accurate: the average ratings were 4.2, 3.3, and 3.8 for GE, Philips, and all images, respectively, for the landmark-based method; and 4.6, 3.7, and 4.2, respectively, for the manual method. The manual registration results were more accurate than the landmark-based registration results (p < 0.0001 for GE, Philips, and all images). Therefore, the manual method produces more accurate registration between T2w and DW images than the landmark-based method.
-
Fusing Facial Features for Face Recognition
Directory of Open Access Journals (Sweden)
Jamal Ahmad Dargham
2012-06-01
Full Text Available Face recognition is an important biometric method because of its potential applications in many fields, such as access control, surveillance, and human-computer interaction. In this paper, a face recognition system that fuses the outputs of three face recognition systems based on Gabor jets is presented. The first system uses the magnitude, the second uses the phase, and the third uses the phase-weighted magnitude of the jets. The jets are generated from facial landmarks selected using three selection methods. It was found out that fusing the facial features gives better recognition rate than either facial feature used individually regardless of the landmark selection method.
-
Feature reconstruction of LFP signals based on PLSR in the neural information decoding study.
Yonghui Dong; Zhigang Shang; Mengmeng Li; Xinyu Liu; Hong Wan
2017-07-01
To solve the problems of Signal-to-Noise Ratio (SNR) and multicollinearity when the Local Field Potential (LFP) signals is used for the decoding of animal motion intention, a feature reconstruction of LFP signals based on partial least squares regression (PLSR) in the neural information decoding study is proposed in this paper. Firstly, the feature information of LFP coding band is extracted based on wavelet transform. Then the PLSR model is constructed by the extracted LFP coding features. According to the multicollinearity characteristics among the coding features, several latent variables which contribute greatly to the steering behavior are obtained, and the new LFP coding features are reconstructed. Finally, the K-Nearest Neighbor (KNN) method is used to classify the reconstructed coding features to verify the decoding performance. The results show that the proposed method can achieve the highest accuracy compared to the other three methods and the decoding effect of the proposed method is robust.
-
Mondal, Ritwik; Devi, N Pemola; Jauhari, R K
2015-06-01
Insect wing morphology has been used in many studies to describe variations among species and populations using traditional morphometrics, and more recently geometric morphometrics. A landmark-based geometric morphometric analysis of the wings of three species of Aedes (Diptera: Culicidae), viz. Ae. aegypti, Ae. albopictus and Ae. pseudotaeniatus, at District Dehradun was conducted belling on the fact that it can provide insight into the population structure, ecology and taxonomic identification. Adult Aedes mosquito specimens were randomly collected using aerial nets and morphologically examined and identified. The landmarks were identified on the basis of landmark based geometric morphometric analysis thin-plate spline (mainly the software tps-Util 1.28; tps-Dig 1.40; tps-Relw 1.53; and tps-Spline 1.20) and integrated morphometrics programme (mainly twogroup win8 and PCA win8) were utilized. In relative warp (RW) analysis, the first two RW of Ae. aegypti accounted for the highest value (95.82%), followed by Ae. pseudotaeniatus (90.89%), while the lowest (90.12%) being recorded for Ae. albopictus. The bending energies of Ae. aegypti and Ae. pseudotaeniatus were quite identical being 0.1882 and 0.1858 respectively, while Ae. albopictus recorded the highest value of 0.9774. The mean difference values of the distances among Aedes species performing Hotelling's T 2 test were significantly high, predicting major differences among the taxa. In PCA analysis, the horizontal and vertical axis summarized 52.41 and 23.30% of variances respectively. The centroid size exhibited significant differences among populations (non-parametric Kruskal-Wallis test, H = 10.56, p < 0.01). It has been marked out that the geometric morphometrics utilizes powerful and comprehensive statistical procedures to analyze the shape differences of a morphological feature, assuming that the studied mosquitoes may represent different genotypes and probably come from one diverse gene pool.
-
A line feature-based camera tracking method applicable to nuclear power plant environment
International Nuclear Information System (INIS)
Yan, Weida; Ishii, Hirotake; Shimoda, Hiroshi; Izumi, Masanori
2014-01-01
Augmented reality, which can support the maintenance and decommissioning work of an NPP to improve efficiency and reduce human error, is expected to be practically used in an NPP. AR has indispensable tracking technology that estimates the 3D position and orientation of users in real time, but because of the complication of the NPP environment, it is difficult for its practial use in the large space of an NPP. This study attempt to develop a tracking method for the practial use in an NPP. Marker tracking is a legacy tracking method, but the preparation work necessary for that method is onerous. Therefore, this study developed and evaluated a natural feature-based camera tracking method that demands less preparation and which is applicable in an NPP environment. This method registers natural features as landmarks. When tracking, the natural features existing in the NPP environment can be registered automatically as landmarks. It is therefore possible to expand the tracking area to cover a wide environment in theory. The evaluation result shows that the proposed tracking method has the possibility to support field work of some kinds in an NPP environment. It is possible to reduce the preparation work necessary for the marker tracking method. (author)
-
Mutual information based feature selection for medical image retrieval
Zhi, Lijia; Zhang, Shaomin; Li, Yan
2018-04-01
In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.
-
An Accurate Integral Method for Vibration Signal Based on Feature Information Extraction
Directory of Open Access Journals (Sweden)
Yong Zhu
2015-01-01
Full Text Available After summarizing the advantages and disadvantages of current integral methods, a novel vibration signal integral method based on feature information extraction was proposed. This method took full advantage of the self-adaptive filter characteristic and waveform correction feature of ensemble empirical mode decomposition in dealing with nonlinear and nonstationary signals. This research merged the superiorities of kurtosis, mean square error, energy, and singular value decomposition on signal feature extraction. The values of the four indexes aforementioned were combined into a feature vector. Then, the connotative characteristic components in vibration signal were accurately extracted by Euclidean distance search, and the desired integral signals were precisely reconstructed. With this method, the interference problem of invalid signal such as trend item and noise which plague traditional methods is commendably solved. The great cumulative error from the traditional time-domain integral is effectively overcome. Moreover, the large low-frequency error from the traditional frequency-domain integral is successfully avoided. Comparing with the traditional integral methods, this method is outstanding at removing noise and retaining useful feature information and shows higher accuracy and superiority.
-
Directory of Open Access Journals (Sweden)
Atiyeh Mortazavi
2016-01-01
Full Text Available High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.
-
Landmarks or panoramas: what do navigating ants attend to for guidance?
Directory of Open Access Journals (Sweden)
Beugnon Guy
2011-08-01
Full Text Available Abstract Background Insects are known to rely on terrestrial landmarks for navigation. Landmarks are used to chart a route or pinpoint a goal. The distant panorama, however, is often thought not to guide navigation directly during a familiar journey, but to act as a contextual cue that primes the correct memory of the landmarks. Results We provided Melophorus bagoti ants with a huge artificial landmark located right near the nest entrance to find out whether navigating ants focus on such a prominent visual landmark for homing guidance. When the landmark was displaced by small or large distances, ant routes were affected differently. Certain behaviours appeared inconsistent with the hypothesis that guidance was based on the landmark only. Instead, comparisons of panoramic images recorded on the field, encompassing both landmark and distal panorama, could explain most aspects of the ant behaviours. Conclusion Ants navigating along a familiar route do not focus on obvious landmarks or filter out distal panoramic cues, but appear to be guided by cues covering a large area of their panoramic visual field, including both landmarks and distal panorama. Using panoramic views seems an appropriate strategy to cope with the complexity of natural scenes and the poor resolution of insects' eyes. The ability to isolate landmarks from the rest of a scene may be beyond the capacity of animals that do not possess a dedicated object-perception visual stream like primates.
-
Palmer, Miquel
2002-01-01
The case described here analyses morphological change at the boundary between ecological and evolutionary scales. The size and shape of 8 populations of two sibling species of tenebrionid beetles (Asida planipennis and A. moraguesi) are analysed using landmark-based methods. The two species differ
-
Norvell, Nicholas G; Korioth, Tom V; Cagna, David R; Versluis, Antheunis
2018-02-08
Artificial markers called fiducials are commonly used to orient digitized surfaces for analysis. However, when these markers are tangible and placed in the region of interest, they may alter surface topography and influence data analysis. The purpose of this in vitro study was to apply a modified digital surface fitting method based on anatomic landmarks to evaluate denture accuracy and to use 2 different denture processing techniques to evaluate the method. The goal was to noninvasively measure and describe any surface differences in denture processing techniques at the intaglio and denture tooth levels. Twenty standardized maxillary complete dentures were waxed on standardized edentulous casts and processed by using acrylic resin compression (COM, n=10) and injection molding (INJ, n=10) methods. Digital scans were recorded of the anatomic surface of the cast, the intaglio and cameo surfaces of the acrylic resin dentures, and the cameo surface of the wax dentures. Three anatomic fiducials were identified on denture intaglio and cast scans and 4 on the cameo surfaces of waxed and acrylic resin denture scans. These fiducials were then used to digitally align the anatomic with the processed intaglio surfaces and the waxed with the processed cameo surfaces. Surface displacements were compared among processed dentures expressed at specific points (9 tissue landmarks and 8 tooth landmarks). The accuracy of surface displacements was assessed by changes in the number and location of anatomic fiducials. The scanning precision and the intraobserver repeatability in the selection of dental landmarks were also determined. For each landmark, the spatial (x, y, and z) mean differences between the 2 processing techniques were calculated for the intaglio and the cameo surfaces and presented on each orthogonal plane. Statistical nonparametric comparison of these means was analyzed with the Mann-Whitney U test (α=.05). Benjamini-Hochberg corrections for multiple comparisons were
-
Directory of Open Access Journals (Sweden)
Hannah eBroadbent
2015-02-01
Full Text Available Visuospatial difficulties in Williams syndrome (WS are well documented. Recently, research has shown that spatial difficulties in WS extend to large-scale space, particularly in coding space using an allocentric frame of reference. Typically developing (TD children and adults predominantly rely on the use of a sequential egocentric strategy to navigate a large-scale route (retracing a sequence of left-right body turns. The aim of this study was to examine whether individuals with WS are able to employ a sequential egocentric strategy to guide learning and the retracing of a route. Forty-eight TD children, aged 5, 7 and 9 years and 18 participants with WS were examined on their ability to learn and retrace routes in two (6-turn virtual environment mazes (with and without landmarks. The ability to successfully retrace a route following the removal of landmarks (use of sequential egocentric coding was also examined.Although in line with TD 5 year-olds when learning a route with landmarks, individuals with WS showed significantly greater detriment when these landmarks were removed, relative to all TD groups. Moreover, the WS group made significantly more errors than all TD groups when learning a route that never contained landmarks. On a perceptual view-matching task, results revealed a high level of performance across groups, indicative of an ability to use this visual information to potentially aid navigation. These findings suggest that individuals with WS rely on landmarks to a greater extent than TD children, both for learning a route and for retracing a recently learned route. TD children, but not individuals with WS, were able to fall back on the use of a sequential egocentric strategy to navigate when landmarks were not present. Only TD children therefore coded sequential route information simultaneously with landmark information. The results are discussed in relation to known atypical cortical development and perceptual-matching abilities
-
Van Haver, Annemieke; De Roo, Karel; De Beule, Matthieu; Van Cauter, Sofie; Audenaert, Emmanuel; Claessens, Tom; Verdonk, Peter
2014-11-01
The authors hypothesise that the trochlear dysplastic distal femur is not only characterised by morphological changes to the trochlea. The purpose of this study is to describe the morphological characteristics of the trochlear dysplastic femur in and outside the trochlear region with a landmark-based 3D analysis. Arthro-CT scans of 20 trochlear dysplastic and 20 normal knees were used to generate 3D models including the cartilage. To rule out size differences, a set of landmarks were defined on the distal femur to isotropically scale the 3D models to a standard size. A predefined series of landmark-based reference planes were applied on the distal femur. With these landmarks and reference planes, a series of previously described characteristics associated with trochlear dysplasia as well as a series of morphometric characteristics were measured. For the previously described characteristics, the analysis replicated highly significant differences between trochlear dysplastic and normal knees. Furthermore, the analysis showed that, when knee size is taken into account, the cut-off values of the trochlear bump and depth would be 1 mm larger in the largest knees compared to the smallest knees. For the morphometric characteristics, the analysis revealed that the trochlear dysplastic femur is also characterised by a 10% smaller intercondylar notch, 6-8% larger posterior condyles (lateral-medial) in the anteroposterior direction and a 6% larger medial condyle in the proximodistal direction compared to a normal femur. This study shows that knee size is important in the application of absolute metric cut-off values and that the posterior femur also shows a significantly different morphology.
-
Directory of Open Access Journals (Sweden)
Xu Zhong
2017-02-01
Full Text Available This article presents a self-localization scheme for indoor mobile robot navigation based on reliable design and recognition of artificial visual landmarks. Each landmark is patterned with a set of concentric circular rings in black and white, which reliably encodes the landmark’s identity under environmental illumination. A mobile robot in navigation uses an onboard camera to capture landmarks in the environment. The landmarks in an image are detected and identified using a bilayer recognition algorithm: A global recognition process initially extracts candidate landmark regions across the whole image and tries to identify enough landmarks; if necessary, a local recognition process locally enhances those unidentified regions of interest influenced by illumination and incompleteness and reidentifies them. The recognized landmarks are used to estimate the position and orientation of the onboard camera in the environment, based on the geometric relationship between the image and environmental frames. The experiments carried out in a real indoor environment show high robustness of the proposed landmark design and recognition scheme to the illumination condition, which leads to reliable and accurate mobile robot localization.
-
Feature extraction and learning using context cue and Rényi entropy based mutual information
DEFF Research Database (Denmark)
Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping
2015-01-01
information. In particular, for feature extraction, we develop a new set of kernel descriptors−Context Kernel Descriptors (CKD), which enhance the original KDES by embedding the spatial context into the descriptors. Context cues contained in the context kernel enforce some degree of spatial consistency, thus...... improving the robustness of CKD. For feature learning and reduction, we propose a novel codebook learning method, based on a Rényi quadratic entropy based mutual information measure called Cauchy-Schwarz Quadratic Mutual Information (CSQMI), to learn a compact and discriminative CKD codebook. Projecting...... as the information about the underlying labels of the CKD using CSQMI. Thus the resulting codebook and reduced CKD are discriminative. We verify the effectiveness of our method on several public image benchmark datasets such as YaleB, Caltech-101 and CIFAR-10, as well as a challenging chicken feet dataset of our own...
-
An Indoor Slam Method Based on Kinect and Multi-Feature Extended Information Filter
Chang, M.; Kang, Z.
2017-09-01
Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.
-
AN INDOOR SLAM METHOD BASED ON KINECT AND MULTI-FEATURE EXTENDED INFORMATION FILTER
Directory of Open Access Journals (Sweden)
M. Chang
2017-09-01
Full Text Available Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.
-
Energy Technology Data Exchange (ETDEWEB)
Dai, Xiubin [College of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210015, China and IDEA Lab, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, 130 Mason Farm Road, Chapel Hill, North Carolina 27510 (United States); Gao, Yaozong [IDEA Lab, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, 130 Mason Farm Road, Chapel Hill, North Carolina 27510 (United States); Shen, Dinggang, E-mail: dgshen@med.unc.edu [IDEA Lab, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, 130 Mason Farm Road, Chapel Hill, North Carolina 27510 and Department of Brain and Cognitive Engineering, Korea University, Seoul (Korea, Republic of)
2015-05-15
Purpose: In image guided radiation therapy, it is crucial to fast and accurately localize the prostate in the daily treatment images. To this end, the authors propose an online update scheme for landmark-guided prostate segmentation, which can fully exploit valuable patient-specific information contained in the previous treatment images and can achieve improved performance in landmark detection and prostate segmentation. Methods: To localize the prostate in the daily treatment images, the authors first automatically detect six anatomical landmarks on the prostate boundary by adopting a context-aware landmark detection method. Specifically, in this method, a two-layer regression forest is trained as a detector for each target landmark. Once all the newly detected landmarks from new treatment images are reviewed or adjusted (if necessary) by clinicians, they are further included into the training pool as new patient-specific information to update all the two-layer regression forests for the next treatment day. As more and more treatment images of the current patient are acquired, the two-layer regression forests can be continually updated by incorporating the patient-specific information into the training procedure. After all target landmarks are detected, a multiatlas random sample consensus (multiatlas RANSAC) method is used to segment the entire prostate by fusing multiple previously segmented prostates of the current patient after they are aligned to the current treatment image. Subsequently, the segmented prostate of the current treatment image is again reviewed (or even adjusted if needed) by clinicians before including it as a new shape example into the prostate shape dataset for helping localize the entire prostate in the next treatment image. Results: The experimental results on 330 images of 24 patients show the effectiveness of the authors’ proposed online update scheme in improving the accuracies of both landmark detection and prostate segmentation
-
International Nuclear Information System (INIS)
Dai, Xiubin; Gao, Yaozong; Shen, Dinggang
2015-01-01
Purpose: In image guided radiation therapy, it is crucial to fast and accurately localize the prostate in the daily treatment images. To this end, the authors propose an online update scheme for landmark-guided prostate segmentation, which can fully exploit valuable patient-specific information contained in the previous treatment images and can achieve improved performance in landmark detection and prostate segmentation. Methods: To localize the prostate in the daily treatment images, the authors first automatically detect six anatomical landmarks on the prostate boundary by adopting a context-aware landmark detection method. Specifically, in this method, a two-layer regression forest is trained as a detector for each target landmark. Once all the newly detected landmarks from new treatment images are reviewed or adjusted (if necessary) by clinicians, they are further included into the training pool as new patient-specific information to update all the two-layer regression forests for the next treatment day. As more and more treatment images of the current patient are acquired, the two-layer regression forests can be continually updated by incorporating the patient-specific information into the training procedure. After all target landmarks are detected, a multiatlas random sample consensus (multiatlas RANSAC) method is used to segment the entire prostate by fusing multiple previously segmented prostates of the current patient after they are aligned to the current treatment image. Subsequently, the segmented prostate of the current treatment image is again reviewed (or even adjusted if needed) by clinicians before including it as a new shape example into the prostate shape dataset for helping localize the entire prostate in the next treatment image. Results: The experimental results on 330 images of 24 patients show the effectiveness of the authors’ proposed online update scheme in improving the accuracies of both landmark detection and prostate segmentation
-
Arterial tree tracking from anatomical landmarks in magnetic resonance angiography scans
O'Neil, Alison; Beveridge, Erin; Houston, Graeme; McCormick, Lynne; Poole, Ian
2014-03-01
This paper reports on arterial tree tracking in fourteen Contrast Enhanced MRA volumetric scans, given the positions of a predefined set of vascular landmarks, by using the A* algorithm to find the optimal path for each vessel based on voxel intensity and a learnt vascular probability atlas. The algorithm is intended for use in conjunction with an automatic landmark detection step, to enable fully automatic arterial tree tracking. The scan is filtered to give two further images using the top-hat transform with 4mm and 8mm cubic structuring elements. Vessels are then tracked independently on the scan in which the vessel of interest is best enhanced, as determined from knowledge of typical vessel diameter and surrounding structures. A vascular probability atlas modelling expected vessel location and orientation is constructed by non-rigidly registering the training scans to the test scan using a 3D thin plate spline to match landmark correspondences, and employing kernel density estimation with the ground truth center line points to form a probability density distribution. Threshold estimation by histogram analysis is used to segment background from vessel intensities. The A* algorithm is run using a linear cost function constructed from the threshold and the vascular atlas prior. Tracking results are presented for all major arteries excluding those in the upper limbs. An improvement was observed when tracking was informed by contextual information, with particular benefit for peripheral vessels.
-
Cephalometric landmark detection in dental x-ray images using convolutional neural networks
Lee, Hansang; Park, Minseok; Kim, Junmo
2017-03-01
In dental X-ray images, an accurate detection of cephalometric landmarks plays an important role in clinical diagnosis, treatment and surgical decisions for dental problems. In this work, we propose an end-to-end deep learning system for cephalometric landmark detection in dental X-ray images, using convolutional neural networks (CNN). For detecting 19 cephalometric landmarks in dental X-ray images, we develop a detection system using CNN-based coordinate-wise regression systems. By viewing x- and y-coordinates of all landmarks as 38 independent variables, multiple CNN-based regression systems are constructed to predict the coordinate variables from input X-ray images. First, each coordinate variable is normalized by the length of either height or width of an image. For each normalized coordinate variable, a CNN-based regression system is trained on training images and corresponding coordinate variable, which is a variable to be regressed. We train 38 regression systems with the same CNN structure on coordinate variables, respectively. Finally, we compute 38 coordinate variables with these trained systems from unseen images and extract 19 landmarks by pairing the regressed coordinates. In experiments, the public database from the Grand Challenges in Dental X-ray Image Analysis in ISBI 2015 was used and the proposed system showed promising performance by successfully locating the cephalometric landmarks within considerable margins from the ground truths.
-
Lee, Moonyoung; Kanavakis, Georgios; Miner, R Matthew
2015-01-01
To identify two novel three-dimensional (3D) cephalometric landmarks and create a novel three-dimensionally based anteroposterior skeletal measurement that can be compared with traditional two-dimensional (2D) cephalometric measurements in patients with Class I and Class II skeletal patterns. Full head cone-beam computed tomography (CBCT) scans of 100 patients with all first molars in occlusion were obtained from a private practice. InvivoDental 3D (version 5.1.6, Anatomage, San Jose, Calif) was used to analyze the CBCT scans in the sagittal and axial planes to create new landmarks and a linear 3D analysis (M measurement) based on maxillary and mandibular centroids. Independent samples t-test was used to compare the mean M measurement to traditional 2D cephalometric measurements, ANB and APDI. Interexaminer and intraexaminer reliability were evaluated using 2D and 3D scatterplots. The M measurement, ANB, and APDI could statistically differentiate between patients with Class I and Class II skeletal patterns (P < .001). The M measurement exhibited a correlation coefficient (r) of -0.79 and 0.88 with APDI and ANB, respectively. The overall centroid landmarks and the M measurement combine 2D and 3D methods of imaging; the measurement itself can distinguish between patients with Class I and Class II skeletal patterns and can serve as a potential substitute for ANB and APDI. The new three-dimensionally based landmarks and measurements are reliable, and there is great potential for future use of 3D analyses for diagnosis and research.
-
Bisch-Knaden, Sonja; Wehner, Rüdiger
2003-03-01
Foraging desert ants, Cataglyphis fortis, encounter different sequences of visual landmarks while navigating by path integration. This paper explores the question whether the storage of landmark information depends on the context in which the landmarks are learned during an ant's foraging journey. Two experimental set-ups were designed in which the ants experienced an artificial landmark panorama that was placed either around the nest entrance (nest marks) or along the vector route leading straight towards the feeder (route marks). The two training paradigms resulted in pronounced differences in the storage characteristics of the acquired landmark information: memory traces of nest marks were much more robust against extinction and/or suppression than those of route marks. In functional terms, this result is in accord with the observation that desert ants encounter new route marks during every foraging run but always pass the same landmarks when approaching the nest entrance.
-
Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid
2014-12-30
Understanding neural functions requires knowledge from analysing electrophysiological data. The process of assigning spikes of a multichannel signal into clusters, called spike sorting, is one of the important problems in such analysis. There have been various automated spike sorting techniques with both advantages and disadvantages regarding accuracy and computational costs. Therefore, developing spike sorting methods that are highly accurate and computationally inexpensive is always a challenge in the biomedical engineering practice. An automatic unsupervised spike sorting method is proposed in this paper. The method uses features extracted by the locality preserving projection (LPP) algorithm. These features afterwards serve as inputs for the landmark-based spectral clustering (LSC) method. Gap statistics (GS) is employed to evaluate the number of clusters before the LSC can be performed. The proposed LPP-LSC is highly accurate and computationally inexpensive spike sorting approach. LPP spike features are very discriminative; thereby boost the performance of clustering methods. Furthermore, the LSC method exhibits its efficiency when integrated with the cluster evaluator GS. The proposed method's accuracy is approximately 13% superior to that of the benchmark combination between wavelet transformation and superparamagnetic clustering (WT-SPC). Additionally, LPP-LSC computing time is six times less than that of the WT-SPC. LPP-LSC obviously demonstrates a win-win spike sorting solution meeting both accuracy and computational cost criteria. LPP and LSC are linear algorithms that help reduce computational burden and thus their combination can be applied into real-time spike analysis. Copyright © 2014 Elsevier B.V. All rights reserved.
-
Remembered landmarks enhance the precision of path integration
Directory of Open Access Journals (Sweden)
Shannon O´Leary
2005-01-01
Full Text Available When navigating by path integration, knowledge of ones position becomes increasingly uncertain as one walks from a known location. This uncertainty decreases if one perceives a known landmark location nearby. We hypothesized that remembering landmarks might serve a similar purpose for path integration as directly perceiving them. If this is true, walking near a remembered landmark location should enhance response consistency in path integration tasks. To test this, we asked participants to view a target and then attempt to walk to it without vision. Some participants saw the target plus a landmark during the preview. Compared with no-landmark trials, response consistency nearly doubled when participants passed near the remembered landmark location. Similar results were obtained when participants could audibly perceive the landmark while walking. A control experiment ruled out perceptual context effects during the preview. We conclude that remembered landmarks can enhance path integration even though they are not directly perceived.
-
Directory of Open Access Journals (Sweden)
Asriyanti Indah Pratiwi
2018-01-01
Full Text Available Sentiment analysis in a movie review is the needs of today lifestyle. Unfortunately, enormous features make the sentiment of analysis slow and less sensitive. Finding the optimum feature selection and classification is still a challenge. In order to handle an enormous number of features and provide better sentiment classification, an information-based feature selection and classification are proposed. The proposed method reduces more than 90% unnecessary features while the proposed classification scheme achieves 96% accuracy of sentiment classification. From the experimental results, it can be concluded that the combination of proposed feature selection and classification achieves the best performance so far.
-
On-Skin Interaction Using Body Landmarks
DEFF Research Database (Denmark)
Steimle, Juergen; Bergstrom-Lehtovirta, Joanna; Weigel, Martin
2017-01-01
The human skin is a promising surface for input to computing devices but differs fundamentally from existing touch-sensitive devices. The authors propose the use of skin landmarks, which offer unique tactile and visual cues, to enhance body-based user interfaces....
-
Fuzzy Mutual Information Based min-Redundancy and Max-Relevance Heterogeneous Feature Selection
Directory of Open Access Journals (Sweden)
Daren Yu
2011-08-01
Full Text Available Feature selection is an important preprocessing step in pattern classification and machine learning, and mutual information is widely used to measure relevance between features and decision. However, it is difficult to directly calculate relevance between continuous or fuzzy features using mutual information. In this paper we introduce the fuzzy information entropy and fuzzy mutual information for computing relevance between numerical or fuzzy features and decision. The relationship between fuzzy information entropy and differential entropy is also discussed. Moreover, we combine fuzzy mutual information with qmin-Redundancy-Max-Relevanceq, qMax-Dependencyq and min-Redundancy-Max-Dependencyq algorithms. The performance and stability of the proposed algorithms are tested on benchmark data sets. Experimental results show the proposed algorithms are effective and stable.
-
An object-oriented feature-based design system face-based detection of feature interactions
International Nuclear Information System (INIS)
Ariffin Abdul Razak
1999-01-01
This paper presents an object-oriented, feature-based design system which supports the integration of design and manufacture by ensuring that part descriptions fully account for any feature interactions. Manufacturing information is extracted from the feature descriptions in the form of volumes and Tool Access Directions, TADs. When features interact, both volumes and TADs are updated. This methodology has been demonstrated by developing a prototype system in which ACIS attributes are used to record feature information within the data structure of the solid model. The system implemented in the C++ programming language and embedded in a menu-driven X-windows user interface to the ACIS 3D Toolkit. (author)
-
Directory of Open Access Journals (Sweden)
Roshan N. RAJAPAKSE
2016-03-01
Full Text Available Accurate identification of anatomical structures from medical imaging data is a significant and critical function in the medical domain. Past studies in this context have mainly utilized two main approaches, the knowledge and learning methodologies based methods. Further, most of previous reported studies have focused on identification of landmarks from lateral X-ray Computed Tomography (CT data, particularly in the field of orthodontics. However, this study focused on extracting cranial landmarks from large sets of cross sectional CT slices using a combined method of the two aforementioned approaches. The proposed method of this study is centered mainly on template data sets, which were created using the actual contour patterns extracted from CT cases for each of the landmarks in consideration. Firstly, these templates were used to devise rules which are a characteristic of the knowledge based method. Secondly, the same template sets were employed to perform template matching related to the learning methodologies approach. The proposed method was tested on two landmarks, the Dorsum sellae and the Pterygoid plate, using CT cases of 5 subjects. The results indicate that, out of the 10 tests, the output images were within the expected range (desired accuracy in 7 instances and acceptable range (near accuracy for 2 instances, thus verifying the effectiveness of the combined template sets centric approach proposed in this study.
-
Cardiac Conduction System: Delineation of Anatomic Landmarks With Multidetector CT
Directory of Open Access Journals (Sweden)
Farhood Saremi
2009-11-01
Full Text Available Major components of the cardiac conduction system including the sinoatrial node (SAN, atrioventricular node (AVN, the His Bundle, and the right and left bundle branches are too small to be directly visualized by multidetector CT (MDCT given the limited spatial resolution of current scanners. However, the related anatomic landmarks and variants of this system a well as the areas with special interest to electrophysiologists can be reliably demonstrated by MDCT. Some of these structures and landmarks include the right SAN artery, right atrial cavotricuspid isthmus, Koch triangle, AVN artery, interatrial muscle bundles, and pulmonary veins. In addition, MDCT has an imperative role in demarcating potential arrhythmogenic structures. The aim of this review will be to assess the extent at which MDCT can outline the described anatomic landmarks and therefore provide crucial information used in clinical practice.
-
The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech
Directory of Open Access Journals (Sweden)
Kun-Ching Wang
2014-09-01
Full Text Available In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS. This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB, to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech.
-
ExpNet: Landmark-Free, Deep, 3D Facial Expressions
Chang, Feng-Ju; Tran, Anh Tuan; Hassner, Tal; Masi, Iacopo; Nevatia, Ram; Medioni, Gerard
2018-01-01
We describe a deep learning based method for estimating 3D facial expression coefficients. Unlike previous work, our process does not relay on facial landmark detection methods as a proxy step. Recent methods have shown that a CNN can be trained to regress accurate and discriminative 3D morphable model (3DMM) representations, directly from image intensities. By foregoing facial landmark detection, these methods were able to estimate shapes for occluded faces appearing in unprecedented in-the-...
-
Feature-based Ontology Mapping from an Information Receivers’ Viewpoint
DEFF Research Database (Denmark)
Glückstad, Fumiko Kano; Mørup, Morten
2012-01-01
This paper compares four algorithms for computing feature-based similarities between concepts respectively possessing a distinctive set of features. The eventual purpose of comparing these feature-based similarity algorithms is to identify a candidate term in a Target Language (TL) that can...... optimally convey the original meaning of a culturally-specific Source Language (SL) concept to a TL audience by aligning two culturally-dependent domain-specific ontologies. The results indicate that the Bayesian Model of Generalization [1] performs best, not only for identifying candidate translation terms...
-
Extra Facial Landmark Localization via Global Shape Reconstruction
Directory of Open Access Journals (Sweden)
Shuqiu Tan
2017-01-01
Full Text Available Localizing facial landmarks is a popular topic in the field of face analysis. However, problems arose in practical applications such as handling pose variations and partial occlusions while maintaining moderate training model size and computational efficiency still challenges current solutions. In this paper, we present a global shape reconstruction method for locating extra facial landmarks comparing to facial landmarks used in the training phase. In the proposed method, the reduced configuration of facial landmarks is first decomposed into corresponding sparse coefficients. Then explicit face shape correlations are exploited to regress between sparse coefficients of different facial landmark configurations. Finally extra facial landmarks are reconstructed by combining the pretrained shape dictionary and the approximation of sparse coefficients. By applying the proposed method, both the training time and the model size of a class of methods which stack local evidences as an appearance descriptor can be scaled down with only a minor compromise in detection accuracy. Extensive experiments prove that the proposed method is feasible and is able to reconstruct extra facial landmarks even under very asymmetrical face poses.
-
Neeser, Rudolph; Ackermann, Rebecca Rogers; Gain, James
2009-09-01
Various methodological approaches have been used for reconstructing fossil hominin remains in order to increase sample sizes and to better understand morphological variation. Among these, morphometric quantitative techniques for reconstruction are increasingly common. Here we compare the accuracy of three approaches--mean substitution, thin plate splines, and multiple linear regression--for estimating missing landmarks of damaged fossil specimens. Comparisons are made varying the number of missing landmarks, sample sizes, and the reference species of the population used to perform the estimation. The testing is performed on landmark data from individuals of Homo sapiens, Pan troglodytes and Gorilla gorilla, and nine hominin fossil specimens. Results suggest that when a small, same-species fossil reference sample is available to guide reconstructions, thin plate spline approaches perform best. However, if no such sample is available (or if the species of the damaged individual is uncertain), estimates of missing morphology based on a single individual (or even a small sample) of close taxonomic affinity are less accurate than those based on a large sample of individuals drawn from more distantly related extant populations using a technique (such as a regression method) able to leverage the information (e.g., variation/covariation patterning) contained in this large sample. Thin plate splines also show an unexpectedly large amount of error in estimating landmarks, especially over large areas. Recommendations are made for estimating missing landmarks under various scenarios. Copyright 2009 Wiley-Liss, Inc.
-
Progressive data transmission for anatomical landmark detection in a cloud.
Sofka, M; Ralovich, K; Zhang, J; Zhou, S K; Comaniciu, D
2012-01-01
In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis. This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data analysis server. The problem of limited bandwidth is solved by a hierarchical sequential detection algorithm that obtains data by progressively transmitting only image regions required for processing. The client sends a request to detect a set of landmarks for region visualization or further analysis. The algorithm running on the data analysis server obtains a coarse level image from the data center and generates landmark location candidates. The candidates are then used to obtain image neighborhood regions at a finer resolution level for further detection. This way, the landmark locations are hierarchically and sequentially detected and refined. Only image regions surrounding landmark location candidates need to be trans- mitted during detection. Furthermore, the image regions are lossy compressed with JPEG 2000. Together, these properties amount to at least 30 times bandwidth reduction while achieving similar accuracy when compared to an algorithm using the original data. The hierarchical sequential algorithm with progressive data transmission considerably reduces bandwidth requirements in cloud-based detection systems.
-
Jimenez-del-Toro, Oscar; Muller, Henning; Krenn, Markus; Gruenberg, Katharina; Taha, Abdel Aziz; Winterstein, Marianne; Eggel, Ivan; Foncubierta-Rodriguez, Antonio; Goksel, Orcun; Jakab, Andres; Kontokotsios, Georgios; Langs, Georg; Menze, Bjoern H.; Fernandez, Tomas Salas; Schaer, Roger
2016-01-01
Variations in the shape and appearance of anatomical structures in medical images are often relevant radiological signs of disease. Automatic tools can help automate parts of this manual process. A cloud-based evaluation framework is presented in this paper including results of benchmarking current state-of-the-art medical imaging algorithms for anatomical structure segmentation and landmark detection: the VISCERAL Anatomy benchmarks. The algorithms are implemented in virtual machines in the ...
-
Accuracy of Automatic Cephalometric Software on Landmark Identification
Anuwongnukroh, N.; Dechkunakorn, S.; Damrongsri, S.; Nilwarat, C.; Pudpong, N.; Radomsutthisarn, W.; Kangern, S.
2017-11-01
This study was to assess the accuracy of an automatic cephalometric analysis software in the identification of cephalometric landmarks. Thirty randomly selected digital lateral cephalograms of patients undergoing orthodontic treatment were used in this study. Thirteen landmarks (S, N, Or, A-point, U1T, U1A, B-point, Gn, Pog, Me, Go, L1T, and L1A) were identified on the digital image by an automatic cephalometric software and on cephalometric tracing by manual method. Superimposition of printed image and manual tracing was done by registration at the soft tissue profiles. The accuracy of landmarks located by the automatic method was compared with that of the manually identified landmarks by measuring the mean differences of distances of each landmark on the Cartesian plane where X and Y coordination axes passed through the center of ear rod. One-Sample T test was used to evaluate the mean differences. Statistically significant mean differences (pmean differences in both horizontal and vertical directions. Small mean differences (mean differences were found for A-point (3.0 4mm) in vertical direction. Only 5 of 13 landmarks (38.46%; S, N, Gn, Pog, and Go) showed no significant mean difference between the automatic and manual landmarking methods. It is concluded that if this automatic cephalometric analysis software is used for orthodontic diagnosis, the orthodontist must correct or modify the position of landmarks in order to increase the accuracy of cephalometric analysis.
-
Wild hummingbirds rely on landmarks not geometry when learning an array of flowers.
Hurly, T Andrew; Fox, Thomas A O; Zwueste, Danielle M; Healy, Susan D
2014-09-01
Rats, birds or fish trained to find a reward in one corner of a small enclosure tend to learn the location of the reward using both nearby visual features and the geometric relationships of corners and walls. Because these studies are conducted under laboratory and thereby unnatural conditions, we sought to determine whether wild, free-living rufous hummingbirds (Selasphorus rufus) learning a single reward location within a rectangular array of flowers would similarly employ both nearby visual landmarks and the geometric relationships of the array. Once subjects had learned the location of the reward, we used test probes in which one or two experimental landmarks were moved or removed in order to reveal how the birds remembered the reward location. The hummingbirds showed no evidence that they used the geometry of the rectangular array of flowers to remember the reward. Rather, they used our experimental landmarks, and possibly nearby, natural landmarks, to orient and navigate to the reward. We believe this to be the first test of the use of rectangular geometry by wild animals, and we recommend further studies be conducted in ecologically relevant conditions in order to help determine how and when animals form complex geometric representations of their local environments.
-
Automated landmark-guided deformable image registration.
Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua
2015-01-07
The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency.
-
Automated landmark-guided deformable image registration
International Nuclear Information System (INIS)
Kearney, Vasant; Chen, Susie; Gu, Xuejun; Chiu, Tsuicheng; Liu, Honghuan; Jiang, Lan; Wang, Jing; Yordy, John; Nedzi, Lucien; Mao, Weihua
2015-01-01
The purpose of this work is to develop an automated landmark-guided deformable image registration (LDIR) algorithm between the planning CT and daily cone-beam CT (CBCT) with low image quality. This method uses an automated landmark generation algorithm in conjunction with a local small volume gradient matching search engine to map corresponding landmarks between the CBCT and the planning CT. The landmarks act as stabilizing control points in the following Demons deformable image registration. LDIR is implemented on graphics processing units (GPUs) for parallel computation to achieve ultra fast calculation. The accuracy of the LDIR algorithm has been evaluated on a synthetic case in the presence of different noise levels and data of six head and neck cancer patients. The results indicate that LDIR performed better than rigid registration, Demons, and intensity corrected Demons for all similarity metrics used. In conclusion, LDIR achieves high accuracy in the presence of multimodality intensity mismatch and CBCT noise contamination, while simultaneously preserving high computational efficiency. (paper)
-
Fayad, Hadi; Pan, Tinsu; Clément, Jean-François; Visvikis, Dimitris
2011-01-01
Purpose Current respiratory motion monitoring devices used for motion synchronization in medical imaging and radiotherapy provide either 1D respiratory signals over a specific region or 3D information based on few external or internal markers. On the other hand, newer technology may offer the potential to monitor the entire patient external surface in real time. The main objective of this study was to assess the motion correlation between such an external patient surface and internal anatomical landmarks motion. Methods Four dimensional Computed Tomography (4D CT) volumes for ten patients were used in this study. Anatomical landmarks were manually selected in the thoracic region across the 4D CT datasets by two experts. The landmarks included normal structures as well as the tumour location. In addition, a distance map representing the entire external patient surface, which corresponds to surfaces acquired by a Time of Flight (ToF) camera or similar devices, was created by segmenting the skin of all 4D CT volumes using a thresholding algorithm. Finally, the correlation between the internal landmarks and external surface motion was evaluated for different regions (placement and size) throughout a patient’s surface. Results Significant variability was observed in the motion of the different parts of the external patient surface. The larger motion magnitude was consistently measured in the central regions of the abdominal and the thoracic areas for the different patient datasets considered. The highest correlation coefficients were observed between the motion of these external surface areas and internal landmarks such as the diaphragm and mediastinum structures as well as the tumour location landmarks (0.8 ± 0.18 and 0.72 ± 0.12 for the abdominal and the thoracic regions respectively). Worse correlation was observed when one considered landmarks not significantly influenced by respiratory motion such as the apex and the sternum. Discussion and conclusions There
-
Comparison of the spatial landmark scatter of various 3D digitalization methods.
Boldt, Florian; Weinzierl, Christian; Hertrich, Klaus; Hirschfelder, Ursula
2009-05-01
The aim of this study was to compare four different three-dimensional digitalization methods on the basis of the complex anatomical surface of a cleft lip and palate plaster cast, and to ascertain their accuracy when positioning 3D landmarks. A cleft lip and palate plaster cast was digitalized with the SCAN3D photo-optical scanner, the OPTIX 400S laser-optical scanner, the Somatom Sensation 64 computed tomography system and the MicroScribe MLX 3-axis articulated-arm digitizer. First, four examiners appraised by individual visual inspection the surface detail reproduction of the three non-tactile digitalization methods in comparison to the reference plaster cast. The four examiners then localized the landmarks five times at intervals of 2 weeks. This involved simply copying, or spatially tracing, the landmarks from a reference plaster cast to each model digitally reproduced by each digitalization method. Statistical analysis of the landmark distribution specific to each method was performed based on the 3D coordinates of the positioned landmarks. Visual evaluation of surface detail conformity assigned the photo-optical digitalization method an average score of 1.5, the highest subjectively-determined conformity (surpassing computer tomographic and laser-optical methods). The tactile scanning method revealed the lowest degree of 3D landmark scatter, 0.12 mm, and at 1.01 mm the lowest maximum 3D landmark scatter; this was followed by the computer tomographic, photo-optical and laser-optical methods (in that order). This study demonstrates that the landmarks' precision and reproducibility are determined by the complexity of the reference-model surface as well as the digital surface quality and individual ability of each evaluator to capture 3D spatial relationships. The differences in the 3D-landmark scatter values and lowest maximum 3D-landmark scatter between the best and the worst methods showed minor differences. The measurement results in this study reveal that it
-
Skophammer, Karen
2010-01-01
This printmaking unit will get students excited about geography and history. In this article, the author describes how her eighth-grade students created a report and a linoleum print of a famous "landmark."
-
International Nuclear Information System (INIS)
Kimura, Momoko; Nawa, Hiroyuki; Yoshida, Kazuhito; Muramatsu, Atsushi; Fuyamada, Mariko; Goto, Shigemi; Ariji, Eiichiro; Tokumori, Kenji; Katsumata, Akitoshi
2009-01-01
We propose a method for evaluating the reliability of a coordinate system based on maxillofacial skeletal landmarks and use it to assess two coordinate systems. Scatter plots and 95% confidence ellipses of an objective landmark were defined as an index for demonstrating the stability of the coordinate system. A head phantom was positioned horizontally in reference to the Frankfurt horizontal and occlusal planes and subsequently scanned once in each position using cone-beam computed tomography. On the three-dimensional images created with a volume-rendering procedure, six dentists twice set two different coordinate systems: coordinate system 1 was defined by the nasion, sella, and basion, and coordinate system 2 was based on the left orbitale, bilateral porions, and basion. The menton was assigned as an objective landmark. The scatter plot and 95% ellipse of the menton indicated the high-level reliability of coordinate system 2. The patterns with the two coordinate systems were similar between data obtained in different head positions. The method presented here may be effective for evaluating the reliability (reproducibility) of coordinate systems based on skeletal landmarks. (author)
-
Correlations of External Landmarks With Internal Structures of the Temporal Bone.
Piromchai, Patorn; Wijewickrema, Sudanthi; Smeds, Henrik; Kennedy, Gregor; O'Leary, Stephen
2015-09-01
The internal anatomy of a temporal bone could be inferred from external landmarks. Mastoid surgery is an important skill that ENT surgeons need to acquire. Surgeons commonly use CT scans as a guide to understanding anatomical variations before surgery. Conversely, in cases where CT scans are not available, or in the temporal bone laboratory where residents are usually not provided with CT scans, it would be beneficial if the internal anatomy of a temporal bone could be inferred from external landmarks. We explored correlations between internal anatomical variations and metrics established to quantify the position of external landmarks that are commonly exposed in the operating room, or the temporal bone laboratory, before commencement of drilling. Mathematical models were developed to predict internal anatomy based on external structures. From an operating room view, the distances between the following external landmarks were observed to have statistically significant correlations with the internal anatomy of a temporal bone: temporal line, external auditory canal, mastoid tip, occipitomastoid suture, and Henle's spine. These structures can be used to infer a low lying dura mater (p = 0.002), an anteriorly located sigmoid sinus (p = 0.006), and a more lateral course of the facial nerve (p external landmarks. The distances between these two landmarks and the operating view external structures were able to further infer the laterality of the facial nerve (p internal structures with a high level of accuracy: the distance from the sigmoid sinus to the posterior external auditory canal (p external landmarks found on the temporal bone. These relationships could be used as a guideline to predict challenges during drilling and choosing appropriate temporal bones for dissection.
-
A cadaveric study of surgical landmarks for retrograde parotidectomy
Directory of Open Access Journals (Sweden)
Wenjie Zhong
2016-08-01
Conclusion: The findings indicate that all three landmarks are useful for surgeons to locate the facial nerve branches during retrograde parotidectomy. Since all three landmarks were consistent indicators for the corresponding facial nerve branches, the surgeon has more than one option should one landmark be obscured by tumors. The optimal landmark is the distance from A to MM because it is shortest and most reliable, followed by RMV to MM, and Z to B.
-
A landmark-based method for the geometrical 3D calibration of scanning microscopes
Energy Technology Data Exchange (ETDEWEB)
Ritter, M.
2007-04-27
This thesis presents a new strategy and a spatial method for the geometric calibration of 3D measurement devices at the micro-range, based on spatial reference structures with nanometersized landmarks (nanomarkers). The new method was successfully applied for the 3D calibration of scanning probe microscopes (SPM) and confocal laser scanning microscopes (CLSM). Moreover, the spatial method was also used for the photogrammetric self-calibration of scanning electron microscopes (SEM). In order to implement the calibration strategy to all scanning microscopes used, the landmark-based principle of reference points often applied at land survey or at close-range applications has been transferred to the nano- and micro-range in the form of nanomarker. In order to function as a support to the nanomarkers, slope-shaped step pyramids have been developed and fabricated by focused ion beam (FIB) induced metal deposition. These FIB produced 3D microstructures have been sized to embrace most of the measurement volume of the scanning microscopes. Additionally, their special design allows the homogenous distribution of the nanomarkers. The nanomarkers were applied onto the support and the plateaus of the slope-step pyramids by FIB etching (milling) as landmarks with as little as several hundreds of nanometers in diameter. The nanomarkers are either of point-, or ring-shaped design. They are optimized so that they can be spatially measured by SPM and CLSM, and, imaged and photogrammetrically analyzed on the basis of SEM data. The centre of the each nanomarker serves as reference point in the measurement data or images. By applying image processing routines, the image (2D) or object (3D) coordinates of each nanomarker has been determined with subpixel accuracy. The correlative analysis of the SPM, CLSM and photogrammetric SEM measurement data after 3D calibration resulted in mean residues in the measured coordinates of as little as 13 nm. Without the coupling factors the mean
-
Santiago, Gabriel F; Susarla, Srinivas M; Al Rakan, Mohammed; Coon, Devin; Rada, Erin M; Sarhane, Karim A; Shores, Jamie T; Bonawitz, Steven C; Cooney, Damon; Sacks, Justin; Murphy, Ryan J; Fishman, Elliot K; Brandacher, Gerald; Lee, W P Andrew; Liacouras, Peter; Grant, Gerald; Armand, Mehran; Gordon, Chad R
2014-05-01
Le Fort-based, maxillofacial allotransplantation is a reconstructive alternative gaining clinical acceptance. However, the vast majority of single-jaw transplant recipients demonstrate less-than-ideal skeletal and dental relationships, with suboptimal aesthetic harmony. The purpose of this study was to investigate reproducible cephalometric landmarks in a large-animal model, where refinement of computer-assisted planning, intraoperative navigational guidance, translational bone osteotomies, and comparative surgical techniques could be performed. Cephalometric landmarks that could be translated into the human craniomaxillofacial skeleton, and that would remain reliable following maxillofacial osteotomies with midfacial alloflap inset, were sought on six miniature swine. Le Fort I- and Le Fort III-based alloflaps were harvested in swine with osteotomies, and all alloflaps were either autoreplanted or transplanted. Cephalometric analyses were performed on lateral cephalograms preoperatively and postoperatively. Critical cephalometric data sets were identified with the assistance of surgical planning and virtual prediction software and evaluated for reliability and translational predictability. Several pertinent landmarks and human analogues were identified, including pronasale, zygion, parietale, gonion, gnathion, lower incisor base, and alveolare. Parietale-pronasale-alveolare and parietale-pronasale-lower incisor base were found to be reliable correlates of sellion-nasion-A point angle and sellion-nasion-B point angle measurements in humans, respectively. There is a set of reliable cephalometric landmarks and measurement angles pertinent for use within a translational large-animal model. These craniomaxillofacial landmarks will enable development of novel navigational software technology, improve cutting guide designs, and facilitate exploration of new avenues for investigation and collaboration.
-
Superpixel-Based Feature for Aerial Image Scene Recognition
Directory of Open Access Journals (Sweden)
Hongguang Li
2018-01-01
Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.
-
Wild rufous hummingbirds use local landmarks to return to rewarded locations.
Pritchard, David J; Scott, Renee D; Healy, Susan D; Hurly, Andrew T
2016-01-01
Animals may remember an important location with reference to one or more visual landmarks. In the laboratory, birds and mammals often preferentially use landmarks near a goal ("local landmarks") to return to that location at a later date. Although we know very little about how animals in the wild use landmarks to remember locations, mammals in the wild appear to prefer to use distant landmarks to return to rewarded locations. To examine what cues wild birds use when returning to a goal, we trained free-living hummingbirds to search for a reward at a location that was specified by three nearby visual landmarks. Following training we expanded the landmark array to test the extent that the birds relied on the local landmarks to return to the reward. During the test the hummingbirds' search was best explained by the birds having used the experimental landmarks to remember the reward location. How the birds used the landmarks was not clear and seemed to change over the course of each test. These wild hummingbirds, then, can learn locations in reference to nearby visual landmarks. Copyright © 2015 Elsevier B.V. All rights reserved.
-
Multimodal Image Alignment via Linear Mapping between Feature Modalities.
Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James
2017-01-01
We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.
-
Naghibi, Tofigh; Hoffmann, Sarah; Pfister, Beat
2015-08-01
Feature subset selection, as a special case of the general subset selection problem, has been the topic of a considerable number of studies due to the growing importance of data-mining applications. In the feature subset selection problem there are two main issues that need to be addressed: (i) Finding an appropriate measure function than can be fairly fast and robustly computed for high-dimensional data. (ii) A search strategy to optimize the measure over the subset space in a reasonable amount of time. In this article mutual information between features and class labels is considered to be the measure function. Two series expansions for mutual information are proposed, and it is shown that most heuristic criteria suggested in the literature are truncated approximations of these expansions. It is well-known that searching the whole subset space is an NP-hard problem. Here, instead of the conventional sequential search algorithms, we suggest a parallel search strategy based on semidefinite programming (SDP) that can search through the subset space in polynomial time. By exploiting the similarities between the proposed algorithm and an instance of the maximum-cut problem in graph theory, the approximation ratio of this algorithm is derived and is compared with the approximation ratio of the backward elimination method. The experiments show that it can be misleading to judge the quality of a measure solely based on the classification accuracy, without taking the effect of the non-optimum search strategy into account.
-
Energy Technology Data Exchange (ETDEWEB)
Durao, Ana Paula Reis; Ferreira, Afonso P. [Dept.of Faculty of Dental Medicine, University of Porto, Porto (Portugal); Morosolli, Aline [Dept.of Surgery, Dentistry School, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul (Brazil); Pittayapat, Pisha [Dept.of Radiology, Faculty of Dentistry, Chulalongkorn University, Bangkok (Thailand); Bolstad, Napat [Dept.of Clinical Dentistry, Faculty of Health Science, UiT The Arctic University of Norway, Tromso (Norway); Jacobs, Reinhilde [Dept.of Oral Imaging Center, OMFS-IMPATH Research Group, Dept. of Imaging and Pathology, Faculty of Medicine, University of Leuven, Leuven (Belgium)
2015-12-15
The aim this study was to compare the accuracy of orthodontists and dentomaxillofacial radiologists in identifying 17 commonly used cephalometric landmarks, and to determine the extent of variability associated with each of those landmarks. Twenty digital lateral cephalometric radiographs were evaluated by two groups of dental specialists, and 17 cephalometric landmarks were identified. The x and y coordinates of each landmark were recorded. The mean value for each landmark was considered the best estimate and used as the standard. Variation in measurements of the distance between landmarks and measurements of the angles associated with certain landmarks was also assessed by a subset of two observers, and intraobserver and interobserver agreement were evaluated. Intraclass correlation coefficients were excellent for intraobserver agreement, but only good for interobserver agreement. The least reliable landmark for orthodontists was the gnathion (Gn) point (standard deviation [SD], 5.92 mm), while the orbitale (Or) was the least reliable landmark (SD, 4.41 mm) for dentomaxillofacial radiologists. Furthermore, the condylion (Co)-Gn plane was the least consistent (SD, 4.43 mm). We established that some landmarks were not as reproducible as others, both horizontally and vertically. The most consistently identified landmark in both groups was the lower incisor border, while the least reliable points were Co, Gn, Or, and the anterior nasal spine. Overall, a lower level of reproducibility in the identification of cephalometric landmarks was observed among orthodontists.
-
International Nuclear Information System (INIS)
Durao, Ana Paula Reis; Ferreira, Afonso P.; Morosolli, Aline; Pittayapat, Pisha; Bolstad, Napat; Jacobs, Reinhilde
2015-01-01
The aim this study was to compare the accuracy of orthodontists and dentomaxillofacial radiologists in identifying 17 commonly used cephalometric landmarks, and to determine the extent of variability associated with each of those landmarks. Twenty digital lateral cephalometric radiographs were evaluated by two groups of dental specialists, and 17 cephalometric landmarks were identified. The x and y coordinates of each landmark were recorded. The mean value for each landmark was considered the best estimate and used as the standard. Variation in measurements of the distance between landmarks and measurements of the angles associated with certain landmarks was also assessed by a subset of two observers, and intraobserver and interobserver agreement were evaluated. Intraclass correlation coefficients were excellent for intraobserver agreement, but only good for interobserver agreement. The least reliable landmark for orthodontists was the gnathion (Gn) point (standard deviation [SD], 5.92 mm), while the orbitale (Or) was the least reliable landmark (SD, 4.41 mm) for dentomaxillofacial radiologists. Furthermore, the condylion (Co)-Gn plane was the least consistent (SD, 4.43 mm). We established that some landmarks were not as reproducible as others, both horizontally and vertically. The most consistently identified landmark in both groups was the lower incisor border, while the least reliable points were Co, Gn, Or, and the anterior nasal spine. Overall, a lower level of reproducibility in the identification of cephalometric landmarks was observed among orthodontists
-
Leonhardt, Sara D; Kaluza, Benjamin F; Wallace, Helen; Heard, Tim A
2016-10-01
To date, no study has investigated how landscape structural (visual) alterations affect navigation and thus homing success in stingless bees. We addressed this question in the Australian stingless bee Tetragonula carbonaria by performing marking, release and re-capture experiments in landscapes differing in habitat homogeneity (i.e., the proportion of elongated ground features typically considered prominent visual landmarks). We investigated how landscape affected the proportion of bees and nectar foragers returning to their hives as well as the earliest time bees and foragers returned. Undisturbed landscapes with few landmarks (that are conspicuous to the human eye) and large proportions of vegetation cover (natural forests) were classified visually/structurally homogeneous, and disturbed landscapes with many landmarks and fragmented or no extensive vegetation cover (gardens and plantations) visually/structurally heterogeneous. We found that proportions of successfully returning nectar foragers and earliest times first bees and foragers returned did not differ between landscapes. However, most bees returned in the visually/structurally most (forest) and least (garden) homogeneous landscape, suggesting that they use other than elongated ground features for navigation and that return speed is primarily driven by resource availability in a landscape.
-
Gender differences in landmark learning for virtual navigation: the role of distance to a goal.
Chamizo, V D; Artigas, A A; Sansa, J; Banterla, F
2011-09-01
We used a new virtual program in two experiments to prepare subjects to perform the Morris water task (www.nesplora.com). The subjects were Psychology students; they were trained to locate a safe platform amidst the presence of four pinpoint landmarks spaced around the edge of the pool (i.e., two landmarks relatively near the platform and two landmarks relatively distant away from it). At the end of the training phase, we administered one test trial without the platform and recorded the amount of time that the students had spent in the platform quadrant. In Experiment 1, we conducted the test trial in the presence of one or two of the distant landmarks. When only one landmark was present during testing, performance fell to chance. However, the men outperformed the women when the two distant landmarks were both present. Experiment 2 replicated the previous results and extended it by showing that no sex differences exist when the searching process is based on the near landmarks. Both the men and the women had similarly good performances when the landmarks were present both individually and together. When present together, an addition effect was found. Far landmark tests favor configural learning processes, whereas near landmark tests favor elemental learning. Our findings suggest that other factors in addition to the use of directional cues can underlie the sex differences in the spatial learning process. Thus, we expand upon previous research in the field. Copyright © 2011 Elsevier B.V. All rights reserved.
-
Daboul, Amro; Ivanovska, Tatyana; Bülow, Robin; Biffar, Reiner; Cardini, Andrea
2018-01-01
Using 3D anatomical landmarks from adult human head MRIs, we assessed the magnitude of inter-operator differences in Procrustes-based geometric morphometric analyses. An in depth analysis of both absolute and relative error was performed in a subsample of individuals with replicated digitization by three different operators. The effect of inter-operator differences was also explored in a large sample of more than 900 individuals. Although absolute error was not unusual for MRI measurements, including bone landmarks, shape was particularly affected by differences among operators, with up to more than 30% of sample variation accounted for by this type of error. The magnitude of the bias was such that it dominated the main pattern of bone and total (all landmarks included) shape variation, largely surpassing the effect of sex differences between hundreds of men and women. In contrast, however, we found higher reproducibility in soft-tissue nasal landmarks, despite relatively larger errors in estimates of nasal size. Our study exemplifies the assessment of measurement error using geometric morphometrics on landmarks from MRIs and stresses the importance of relating it to total sample variance within the specific methodological framework being used. In summary, precise landmarks may not necessarily imply negligible errors, especially in shape data; indeed, size and shape may be differentially impacted by measurement error and different types of landmarks may have relatively larger or smaller errors. Importantly, and consistently with other recent studies using geometric morphometrics on digital images (which, however, were not specific to MRI data), this study showed that inter-operator biases can be a major source of error in the analysis of large samples, as those that are becoming increasingly common in the 'era of big data'.
-
Energy Technology Data Exchange (ETDEWEB)
Gamble, Jennifer; Lagravere, Manuel O.; Major, Paul W.; Heo, Giseon [University of Alberta, Edmonton (Canada)
2012-03-15
To describe a statistical method of three-dimensional landmark configuration data and apply it to an orthodontic data set comparing two types of rapid maxillary expansion (RME) treatments. Landmark configurations obtained from cone beam CT scans were used to represent patients in two types (please describe what were two types) of RME groups and a control group over four time points. A method using tools from persistent homology and dimensionality reduction is presented and used to identify variability between the subjects. The analysis was in agreement with previous results using conventional methods, which found significant differences between treatment groups and the control, but no distinction between the types of treatment. Additionally, it was found that second molar eruption varied considerably between the subjects, and this has not been evaluated in previous analyses. This method of analysis allows entire configurations to be considered as a whole, and does not require specific inter-landmark distances or angles to be selected. Sources of variability present themselves, without having to be individually sought after. This method is suggested as an additional tool for the analysis of landmark configuration data.
-
PEOPLE'S EVALUATION TOWARDS MEDIA FAÇADE AS NEW URBAN LANDMARKS AT NIGHT
Directory of Open Access Journals (Sweden)
Elyas Vahedi Moghaddam
2016-04-01
Full Text Available This paper attempts to help designers to turn a building into media facade as an attractive landmark for people’s urban night life. The literature survey points towards being dynamic and interactive with observers as the two quality dimensions for implementing this emerging lighting technology. Based on a survey of eleven selected media facades using video films to 250 students and staff at a public university, results identified twelve attributes for these two qualities. However, item analysis and exploratory factor analysis of the results determined only ten attributes actually support people’s attention towards media facade. The attributes of unique landmark, different nocturnal appearance, dynamic colour, informative lighting, artistic lighting performance, on going process, and dynamic advertisement could be categorized under the visual quality dimension. On the other hand, attributes of covert interaction, overt interaction, and predesigned interaction could be categorized under the interactive quality dimension. This study contributes in prioritizing visual qualities for guiding the attractiveness of buildings’ appearances at night, hence enabling the creation of new dynamic urban spaces when designing buildings.
-
A low-cost test-bed for real-time landmark tracking
Csaszar, Ambrus; Hanan, Jay C.; Moreels, Pierre; Assad, Christopher
2007-04-01
A low-cost vehicle test-bed system was developed to iteratively test, refine and demonstrate navigation algorithms before attempting to transfer the algorithms to more advanced rover prototypes. The platform used here was a modified radio controlled (RC) car. A microcontroller board and onboard laptop computer allow for either autonomous or remote operation via a computer workstation. The sensors onboard the vehicle represent the types currently used on NASA-JPL rover prototypes. For dead-reckoning navigation, optical wheel encoders, a single axis gyroscope, and 2-axis accelerometer were used. An ultrasound ranger is available to calculate distance as a substitute for the stereo vision systems presently used on rovers. The prototype also carries a small laptop computer with a USB camera and wireless transmitter to send real time video to an off-board computer. A real-time user interface was implemented that combines an automatic image feature selector, tracking parameter controls, streaming video viewer, and user generated or autonomous driving commands. Using the test-bed, real-time landmark tracking was demonstrated by autonomously driving the vehicle through the JPL Mars yard. The algorithms tracked rocks as waypoints. This generated coordinates calculating relative motion and visually servoing to science targets. A limitation for the current system is serial computing-each additional landmark is tracked in order-but since each landmark is tracked independently, if transferred to appropriate parallel hardware, adding targets would not significantly diminish system speed.
-
Dynamic facial expression recognition based on geometric and texture features
Li, Ming; Wang, Zengfu
2018-04-01
Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.
-
Spatiotemporal Features for Asynchronous Event-based Data
Directory of Open Access Journals (Sweden)
Xavier eLagorce
2015-02-01
Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.
-
Directory of Open Access Journals (Sweden)
Shuping Cai
2018-03-01
Full Text Available Weather information is an important factor in short-term load forecasting (STLF. However, for a long time, more importance has always been attached to forecasting models instead of other processes such as the introduction of weather factors or feature selection for STLF. The main aim of this paper is to develop a novel methodology based on Fisher information for meteorological variables introduction and variable selection in STLF. Fisher information computation for one-dimensional and multidimensional weather variables is first described, and then the introduction of meteorological factors and variables selection for STLF models are discussed in detail. On this basis, different forecasting models with the proposed methodology are established. The proposed methodology is implemented on real data obtained from Electric Power Utility of Zhenjiang, Jiangsu Province, in southeast China. The results show the advantages of the proposed methodology in comparison with other traditional ones regarding prediction accuracy, and it has very good practical significance. Therefore, it can be used as a unified method for introducing weather variables into STLF models, and selecting their features.
-
Directory of Open Access Journals (Sweden)
Li Yao
2016-01-01
Full Text Available Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.
-
Mitsuhiro Isaka; Masahiko Befu; Nami Matsubara; Mayuko Ishikawa; Yurie Arase; Toshiyuki Tsuyama; Akiko Doi; Shinichi Namba
2014-01-01
Canine medial patellar luxation (MPL) is a very common orthopedic disease in small animals. Because the pathophysiology of this disease involves various pathways, the surgical techniques and results vary according to the veterinarian. Further, the landmark for block recession is not completely clear. We retrospectively evaluated 75 dogs (107 limbs) with MPL in whom our landmark for block recession was used from July 2008 to May 2013. Information regarding the breed, age, sex, body weight, bod...
-
GENDER RECOGNITION BASED ON SIFT FEATURES
Sahar Yousefi; Morteza Zahedi
2011-01-01
This paper proposes a robust approach for face detection and gender classification in color images. Previous researches about gender recognition suppose an expensive computational and time-consuming pre-processing step in order to alignment in which face images are aligned so that facial landmarks like eyes, nose, lips, chin are placed in uniform locations in image. In this paper, a novel technique based on mathematical analysis is represented in three stages that eliminates align...
-
Feature-based tolerancing for intelligent inspection process definition
International Nuclear Information System (INIS)
Brown, C.W.
1993-07-01
This paper describes a feature-based tolerancing capability that complements a geometric solid model with an explicit representation of conventional and geometric tolerances. This capability is focused on supporting an intelligent inspection process definition system. The feature-based tolerance model's benefits include advancing complete product definition initiatives (e.g., STEP -- Standard for Exchange of Product model dam), suppling computer-integrated manufacturing applications (e.g., generative process planning and automated part programming) with product definition information, and assisting in the solution of measurement performance issues. A feature-based tolerance information model was developed based upon the notion of a feature's toleranceable aspects and describes an object-oriented scheme for representing and relating tolerance features, tolerances, and datum reference frames. For easy incorporation, the tolerance feature entities are interconnected with STEP solid model entities. This schema will explicitly represent the tolerance specification for mechanical products, support advanced dimensional measurement applications, and assist in tolerance-related methods divergence issues
-
Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.
Suresh, Krithika; Taylor, Jeremy M G; Spratt, Daniel E; Daignault, Stephanie; Tsodikov, Alexander
2017-11-01
Dynamic prediction incorporates time-dependent marker information accrued during follow-up to improve personalized survival prediction probabilities. At any follow-up, or "landmark", time, the residual time distribution for an individual, conditional on their updated marker values, can be used to produce a dynamic prediction. To satisfy a consistency condition that links dynamic predictions at different time points, the residual time distribution must follow from a prediction function that models the joint distribution of the marker process and time to failure, such as a joint model. To circumvent the assumptions and computational burden associated with a joint model, approximate methods for dynamic prediction have been proposed. One such method is landmarking, which fits a Cox model at a sequence of landmark times, and thus is not a comprehensive probability model of the marker process and the event time. Considering an illness-death model, we derive the residual time distribution and demonstrate that the structure of the Cox model baseline hazard and covariate effects under the landmarking approach do not have simple form. We suggest some extensions of the landmark Cox model that should provide a better approximation. We compare the performance of the landmark models with joint models using simulation studies and cognitive aging data from the PAQUID study. We examine the predicted probabilities produced under both methods using data from a prostate cancer study, where metastatic clinical failure is a time-dependent covariate for predicting death following radiation therapy. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
-
Feature-Based and String-Based Models for Predicting RNA-Protein Interaction
Directory of Open Access Journals (Sweden)
Donald Adjeroh
2018-03-01
Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.
-
Schmidt, Jodi L; Cole, Theodore M; Silcox, Mary T
2011-08-01
Previous study of the ear ossicles in Primates has demonstrated that they vary on both functional and phylogenetic bases. Such studies have generally employed two-dimensional linear measurements rather than three-dimensional data. The availability of Ultra- high-resolution X-ray computed tomography (UhrCT) has made it possible to accurately image the ossicles so that broadly accepted methodologies for acquiring and studying morphometric data can be applied. Using UhrCT data also allows for the ossicular chain to be studied in anatomical position, so that it is possible to consider the spatial and size relationships of all three bones. One issue impeding the morphometric study of the ear ossicles is a lack of broadly recognized landmarks. Distinguishing landmarks on the ossicles is difficult in part because there are only two areas of articulation in the ossicular chain, one of which (the malleus/incus articulation) has a complex three-dimensional form. A measurement error study is presented demonstrating that a suite of 16 landmarks can be precisely located on reconstructions of the ossicles from UhrCT data. Estimates of measurement error showed that most landmarks were highly replicable, with an average CV for associated interlandmark distances of less than 3%. The positions of these landmarks are chosen to reflect not only the overall shape of the bones in the chain and their relative positions, but also functional parameters. This study should provide a basis for further examination of the smallest bones in the body in three dimensions. Copyright © 2011 Wiley-Liss, Inc.
-
Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin
2016-09-01
Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.
-
Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia
2016-01-01
An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996
-
Directory of Open Access Journals (Sweden)
Seyed Mostafa Mousavi Kahaki
Full Text Available An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new descriptor's similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence.
-
International Nuclear Information System (INIS)
Pittayapat, Pisha; Jacobs, Reinhilde; Odri, Guillaume A.; De Faria Vasconcelos, Karla; Willems, Guy; Olszewski, Raphael
2015-01-01
This study was performed to assess the reproducibility of identifying the sella turcica landmark in a three-dimensional (3D) model by using a new sella-specific landmark reference system. Thirty-two cone-beam computed tomographic scans (3D Accuitomo 170, J. Morita, Kyoto, Japan) were retrospectively collected. The 3D data were exported into the Digital Imaging and Communications in Medicine standard and then imported into the Maxilim software (Medicim NV, Sint-Niklaas, Belgium) to create 3D surface models. Five observers identified four osseous landmarks in order to create the reference frame and then identified two sella landmarks. The x, y, and z coordinates of each landmark were exported. The observations were repeated after four weeks. Statistical analysis was performed using the multiple paired t-test with Bonferroni correction (intraobserver precision: p<0.005, interobserver precision: p<0.0011). The intraobserver mean precision of all landmarks was <1 mm. Significant differences were found when comparing the intraobserver precision of each observer (p<0.005). For the sella landmarks, the intraobserver mean precision ranged from 0.43±0.34 mm to 0.51±0.46 mm. The intraobserver reproducibility was generally good. The overall interobserver mean precision was <1 mm. Significant differences between each pair of observers for all anatomical landmarks were found (p<0.0011). The interobserver reproducibility of sella landmarks was good, with >50% precision in locating the landmark within 1 mm. A newly developed reference system offers high precision and reproducibility for sella turcica identification in a 3D model without being based on two-dimensional images derived from 3D data.
-
Energy Technology Data Exchange (ETDEWEB)
Pittayapat, Pisha; Jacobs, Reinhilde [University Hospitals Leuven, University of Leuven, Leuven (Belgium); Odri, Guillaume A. [Service de Chirurgie Orthopedique et Traumatologique, Centre Hospitalier Regional d' Orleans, Orleans Cedex2 (France); De Faria Vasconcelos, Karla [Dept. of Oral Diagnosis, Division of Oral Radiology, Piracicaba Dental School, University of Campinas, Sao Paulo (Brazil); Willems, Guy [Dept. of Oral Health Sciences, Orthodontics, KU Leuven and Dentistry, University Hospitals Leuven, University of Leuven, Leuven (Belgium); Olszewski, Raphael [Dept. of Oral and Maxillofacial Surgery, Cliniques Universitaires Saint Luc, Universite Catholique de Louvain, Brussels (Belgium)
2015-03-15
This study was performed to assess the reproducibility of identifying the sella turcica landmark in a three-dimensional (3D) model by using a new sella-specific landmark reference system. Thirty-two cone-beam computed tomographic scans (3D Accuitomo 170, J. Morita, Kyoto, Japan) were retrospectively collected. The 3D data were exported into the Digital Imaging and Communications in Medicine standard and then imported into the Maxilim software (Medicim NV, Sint-Niklaas, Belgium) to create 3D surface models. Five observers identified four osseous landmarks in order to create the reference frame and then identified two sella landmarks. The x, y, and z coordinates of each landmark were exported. The observations were repeated after four weeks. Statistical analysis was performed using the multiple paired t-test with Bonferroni correction (intraobserver precision: p<0.005, interobserver precision: p<0.0011). The intraobserver mean precision of all landmarks was <1 mm. Significant differences were found when comparing the intraobserver precision of each observer (p<0.005). For the sella landmarks, the intraobserver mean precision ranged from 0.43±0.34 mm to 0.51±0.46 mm. The intraobserver reproducibility was generally good. The overall interobserver mean precision was <1 mm. Significant differences between each pair of observers for all anatomical landmarks were found (p<0.0011). The interobserver reproducibility of sella landmarks was good, with >50% precision in locating the landmark within 1 mm. A newly developed reference system offers high precision and reproducibility for sella turcica identification in a 3D model without being based on two-dimensional images derived from 3D data.
-
Conditional Mutual Information Based Feature Selection for Classification Task
Czech Academy of Sciences Publication Activity Database
Novovičová, Jana; Somol, Petr; Haindl, Michal; Pudil, Pavel
2007-01-01
Roč. 45, č. 4756 (2007), s. 417-426 ISSN 0302-9743 R&D Projects: GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Pattern classification * feature selection * conditional mutual information * text categorization Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.402, year: 2005
-
Westerbeek, Hans; Maes, Alfons
2013-01-01
Landmarks are basic ingredients in route descriptions. They often mark choice points: locations where travellers choose from different options how to continue the route. This study focuses on one of the loose ends in the taxonomy of landmarks. In a memory-based production experiment in which
-
Monocular SLAM for autonomous robots with enhanced features initialization.
Guerra, Edmundo; Munguia, Rodrigo; Grau, Antoni
2014-04-02
This work presents a variant approach to the monocular SLAM problem focused in exploiting the advantages of a human-robot interaction (HRI) framework. Based upon the delayed inverse-depth feature initialization SLAM (DI-D SLAM), a known monocular technique, several but crucial modifications are introduced taking advantage of data from a secondary monocular sensor, assuming that this second camera is worn by a human. The human explores an unknown environment with the robot, and when their fields of view coincide, the cameras are considered a pseudo-calibrated stereo rig to produce estimations for depth through parallax. These depth estimations are used to solve a related problem with DI-D monocular SLAM, namely, the requirement of a metric scale initialization through known artificial landmarks. The same process is used to improve the performance of the technique when introducing new landmarks into the map. The convenience of the approach taken to the stereo estimation, based on SURF features matching, is discussed. Experimental validation is provided through results from real data with results showing the improvements in terms of more features correctly initialized, with reduced uncertainty, thus reducing scale and orientation drift. Additional discussion in terms of how a real-time implementation could take advantage of this approach is provided.
-
Sled, Elizabeth A.; Sheehy, Lisa M.; Felson, David T.; Costigan, Patrick A.; Lam, Miu; Cooke, T. Derek V.
2010-01-01
The objective of the study was to evaluate the reliability of frontal plane lower limb alignment measures using a landmark-based method by (1) comparing inter- and intra-reader reliability between measurements of alignment obtained manually with those using a computer program, and (2) determining inter- and intra-reader reliability of computer-assisted alignment measures from full-limb radiographs. An established method for measuring alignment was used, involving selection of 10 femoral and tibial bone landmarks. 1) To compare manual and computer methods, we used digital images and matching paper copies of five alignment patterns simulating healthy and malaligned limbs drawn using AutoCAD. Seven readers were trained in each system. Paper copies were measured manually and repeat measurements were performed daily for 3 days, followed by a similar routine with the digital images using the computer. 2) To examine the reliability of computer-assisted measures from full-limb radiographs, 100 images (200 limbs) were selected as a random sample from 1,500 full-limb digital radiographs which were part of the Multicenter Osteoarthritis (MOST) Study. Three trained readers used the software program to measure alignment twice from the batch of 100 images, with two or more weeks between batch handling. Manual and computer measures of alignment showed excellent agreement (intraclass correlations [ICCs] 0.977 – 0.999 for computer analysis; 0.820 – 0.995 for manual measures). The computer program applied to full-limb radiographs produced alignment measurements with high inter- and intra-reader reliability (ICCs 0.839 – 0.998). In conclusion, alignment measures using a bone landmark-based approach and a computer program were highly reliable between multiple readers. PMID:19882339
-
INTEGRATED INFORMATION SYSTEM ARCHITECTURE PROVIDING BEHAVIORAL FEATURE
Directory of Open Access Journals (Sweden)
Vladimir N. Shvedenko
2016-11-01
Full Text Available The paper deals with creation of integrated information system architecture capable of supporting management decisions using behavioral features. The paper considers the architecture of information decision support system for production system management. The behavioral feature is given to an information system, and it ensures extraction, processing of information, management decision-making with both automated and automatic modes of decision-making subsystem being permitted. Practical implementation of information system with behavior is based on service-oriented architecture: there is a set of independent services in the information system that provides data of its subsystems or data processing by separate application under the chosen variant of the problematic situation settlement. For creation of integrated information system with behavior we propose architecture including the following subsystems: data bus, subsystem for interaction with the integrated applications based on metadata, business process management subsystem, subsystem for the current state analysis of the enterprise and management decision-making, behavior training subsystem. For each problematic situation a separate logical layer service is created in Unified Service Bus handling problematic situations. This architecture reduces system information complexity due to the fact that with a constant amount of system elements the number of links decreases, since each layer provides communication center of responsibility for the resource with the services of corresponding applications. If a similar problematic situation occurs, its resolution is automatically removed from problem situation metamodel repository and business process metamodel of its settlement. In the business process performance commands are generated to the corresponding centers of responsibility to settle a problematic situation.
-
Auger, Stephen D; Zeidman, Peter; Maguire, Eleanor A
2017-09-01
Human beings differ considerably in their ability to orient and navigate within the environment, but it has been difficult to determine specific causes of these individual differences. Permanent, stable landmarks are thought to be crucial for building a mental representation of an environment. Poor, compared to good, navigators have been shown to have difficulty identifying permanent landmarks, with a concomitant reduction in functional MRI (fMRI) activity in the retrosplenial cortex. However, a clear association between navigation ability and the learning of permanent landmarks has not been established. Here we tested for such a link. We had participants learn a virtual reality environment by repeatedly moving through it during fMRI scanning. The environment contained landmarks of which participants had no prior experience, some of which remained fixed in their locations while others changed position each time they were seen. After the fMRI learning phase, we divided participants into good and poor navigators based on their ability to find their way in the environment. The groups were closely matched on a range of cognitive and structural brain measures. Examination of the learning phase during scanning revealed that, while good and poor navigators learned to recognise the environment's landmarks at a similar rate, poor navigators were impaired at registering whether landmarks were stable or transient, and this was associated with reduced engagement of the retrosplenial cortex. Moreover, a mediation analysis showed that there was a significant effect of landmark permanence learning on navigation performance mediated through retrosplenial cortex activity. We conclude that a diminished ability to process landmark permanence may be a contributory factor to sub-optimal navigation, and could be related to the level of retrosplenial cortex engagement. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
-
[New international classification of corneal dystrophies and clinical landmarks].
Lisch, W; Seitz, B
2008-07-01
The International Committee on Classification of Corneal Dystrophies, briefly IC (3)D, was founded with the sponsorship of the American Cornea Society and the American Academy of Ophthalmology in July 2005. This committee consists of 17 corneal experts (1) from USA, Asia and Europe. The goal of this group was to develop a new, internationally accepted classification of corneal dystrophies (CD) based on modern clinical, histological and genetical knowledge. The aim of the new classification should be to avoid wrong interpretations and misnomers of the different forms of CD. The IC (3)D extensive manuscript is in press as Supplement publication in the journal "Cornea". The 25 different CD are divided in four categories by clinical and genetical knowledge. Additionally, templates for each type of CD are included. Finally, many typical color slit-lamp photos are presented in the publication together with essential references and current genetical results in tabular form. As members of IC (3)D the authors present a clinical landmark survey of the different corneal dystrophies. The ophthalmologist is the first to examine and to diagnose a new patient with a probable CD at the slit-lamp. Our elaborated table of landmarks is supposed to be a "bridge" for the ophthalmologist to precisely define the corneal opacities of a presumed CD. This "bridge" makes it easier for them to study the IC (3)D Supplement publication and to get more information including adequate differential diagnosis.
-
Continuous Indoor Positioning Fusing WiFi, Smartphone Sensors and Landmarks.
Deng, Zhi-An; Wang, Guofeng; Qin, Danyang; Na, Zhenyu; Cui, Yang; Chen, Juan
2016-09-05
To exploit the complementary strengths of WiFi positioning, pedestrian dead reckoning (PDR), and landmarks, we propose a novel fusion approach based on an extended Kalman filter (EKF). For WiFi positioning, unlike previous fusion approaches setting measurement noise parameters empirically, we deploy a kernel density estimation-based model to adaptively measure the related measurement noise statistics. Furthermore, a trusted area of WiFi positioning defined by fusion results of previous step and WiFi signal outlier detection are exploited to reduce computational cost and improve WiFi positioning accuracy. For PDR, we integrate a gyroscope, an accelerometer, and a magnetometer to determine the user heading based on another EKF model. To reduce accumulation error of PDR and enable continuous indoor positioning, not only the positioning results but also the heading estimations are recalibrated by indoor landmarks. Experimental results in a realistic indoor environment show that the proposed fusion approach achieves substantial positioning accuracy improvement than individual positioning approaches including PDR and WiFi positioning.
-
Spatiotopic updating of visual feature information.
Zimmermann, Eckart; Weidner, Ralph; Fink, Gereon R
2017-10-01
Saccades shift the retina with high-speed motion. In order to compensate for the sudden displacement, the visuomotor system needs to combine saccade-related information and visual metrics. Many neurons in oculomotor but also in visual areas shift their receptive field shortly before the execution of a saccade (Duhamel, Colby, & Goldberg, 1992; Nakamura & Colby, 2002). These shifts supposedly enable the binding of information from before and after the saccade. It is a matter of current debate whether these shifts are merely location based (i.e., involve remapping of abstract spatial coordinates) or also comprise information about visual features. We have recently presented fMRI evidence for a feature-based remapping mechanism in visual areas V3, V4, and VO (Zimmermann, Weidner, Abdollahi, & Fink, 2016). In particular, we found fMRI adaptation in cortical regions representing a stimulus' retinotopic as well as its spatiotopic position. Here, we asked whether spatiotopic adaptation exists independently from retinotopic adaptation and which type of information is behaviorally more relevant after saccade execution. We first adapted at the saccade target location only and found a spatiotopic tilt aftereffect. Then, we simultaneously adapted both the fixation and the saccade target location but with opposite tilt orientations. As a result, adaptation from the fixation location was carried retinotopically to the saccade target position. The opposite tilt orientation at the retinotopic location altered the effects induced by spatiotopic adaptation. More precisely, it cancelled out spatiotopic adaptation at the saccade target location. We conclude that retinotopic and spatiotopic visual adaptation are independent effects.
-
UAV Control on the Basis of 3D Landmark Bearing-Only Observations.
Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry
2015-11-27
The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks' position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations.
-
Route and landmark selection tool (RULST) : user's manual.; TOPICAL
International Nuclear Information System (INIS)
Widing, M. A.
2002-01-01
The Route and Landmark Selection Tool (RULST) is a software program designed to assist military planners in defining geographical objects, such as routes, landmarks, spurs, and yards, at a given facility. Argonne National Laboratory is currently developing a prototype of this tool for use by the Military Traffic Management Command Transportation Engineering Agency (MTMCTEA). The primary objective of RULST is to populate database tables of facility objects for use in MTMCTEA models. RULST defines facility data for use in models such as Port Simulation (PORTSIM) and Transportation System Capability (TRANSCAP), which simulate the transportation of equipment through ports and military installations. The main purpose of RULST is to allow you to specify the relationships between landmarks and routes. The nodes, links, and landmarks that describe a facility are often predefined on the basis of the layout of the physical site
-
A Distributed Feature-based Environment for Collaborative Design
Directory of Open Access Journals (Sweden)
Wei-Dong Li
2003-02-01
Full Text Available This paper presents a client/server design environment based on 3D feature-based modelling and Java technologies to enable design information to be shared efficiently among members within a design team. In this environment, design tasks and clients are organised through working sessions generated and maintained by a collaborative server. The information from an individual design client during a design process is updated and broadcast to other clients in the same session through an event-driven and call-back mechanism. The downstream manufacturing analysis modules can be wrapped as agents and plugged into the open environment to support the design activities. At the server side, a feature-feature relationship is established and maintained to filter the varied information of a working part, so as to facilitate efficient information update during the design process.
-
Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images
Directory of Open Access Journals (Sweden)
R. Youmaran
2012-01-01
Full Text Available This paper develops an approach to measure the information content in a biometric feature representation of iris images. In this context, the biometric feature information is calculated using the relative entropy between the intraclass and interclass feature distributions. The collected data is regularized using a Gaussian model of the feature covariances in order to practically measure the biometric information with limited data samples. An example of this method is shown for iris templates processed using Principal-Component Analysis- (PCA- and Independent-Component Analysis- (ICA- based feature decomposition schemes. From this, the biometric feature information is calculated to be approximately 278 bits for PCA and 288 bits for ICA iris features using Masek's iris recognition scheme. This value approximately matches previous estimates of iris information content.
-
International Nuclear Information System (INIS)
Shi Jiazheng; Sahiner, Berkman; Chan Heangping; Ge Jun; Hadjiiski, Lubomir; Helvie, Mark A.; Nees, Alexis; Wu Yita; Wei Jun; Zhou Chuan; Zhang Yiheng; Cui Jing
2008-01-01
Computer-aided diagnosis (CAD) for characterization of mammographic masses as malignant or benign has the potential to assist radiologists in reducing the biopsy rate without increasing false negatives. The purpose of this study was to develop an automated method for mammographic mass segmentation and explore new image based features in combination with patient information in order to improve the performance of mass characterization. The authors' previous CAD system, which used the active contour segmentation, and morphological, textural, and spiculation features, has achieved promising results in mass characterization. The new CAD system is based on the level set method and includes two new types of image features related to the presence of microcalcifications with the mass and abruptness of the mass margin, and patient age. A linear discriminant analysis (LDA) classifier with stepwise feature selection was used to merge the extracted features into a classification score. The classification accuracy was evaluated using the area under the receiver operating characteristic curve. The authors' primary data set consisted of 427 biopsy-proven masses (200 malignant and 227 benign) in 909 regions of interest (ROIs) (451 malignant and 458 benign) from multiple mammographic views. Leave-one-case-out resampling was used for training and testing. The new CAD system based on the level set segmentation and the new mammographic feature space achieved a view-based A z value of 0.83±0.01. The improvement compared to the previous CAD system was statistically significant (p=0.02). When patient age was included in the new CAD system, view-based and case-based A z values were 0.85±0.01 and 0.87±0.02, respectively. The study also demonstrated the consistency of the newly developed CAD system by evaluating the statistics of the weights of the LDA classifiers in leave-one-case-out classification. Finally, an independent test on the publicly available digital database for screening
-
Frigeri, Thomas; Rhoton, Albert; Paglioli, Eliseu; Azambuja, Ney
2014-10-01
To establish preoperatively the localization of the cortical projection of the inferior choroidal point (ICP) and use it as a reliable landmark when approaching the temporal horn through a middle temporal gyrus access. To review relevant anatomical features regarding selective amigdalohippocampectomy (AH) for treatment of mesial temporal lobe epilepsy (MTLE). The cortical projection of the inferior choroidal point was used in more than 300 surgeries by one authors as a reliable landmark to reach the temporal horn. In the laboratory, forty cerebral hemispheres were examined. The cortical projection of the ICP is a reliable landmark for reaching the temporal horn.
-
Salo, Zoryana; Beek, Maarten; Wright, David; Whyne, Cari Marisa
2015-04-13
Current methods for the development of pelvic finite element (FE) models generally are based upon specimen specific computed tomography (CT) data. This approach has traditionally required segmentation of CT data sets, which is time consuming and necessitates high levels of user intervention due to the complex pelvic anatomy. The purpose of this research was to develop and assess CT landmark-based semi-automated mesh morphing and mapping techniques to aid the generation and mechanical analysis of specimen-specific FE models of the pelvis without the need for segmentation. A specimen-specific pelvic FE model (source) was created using traditional segmentation methods and morphed onto a CT scan of a different (target) pelvis using a landmark-based method. The morphed model was then refined through mesh mapping by moving the nodes to the bone boundary. A second target model was created using traditional segmentation techniques. CT intensity based material properties were assigned to the morphed/mapped model and to the traditionally segmented target models. Models were analyzed to evaluate their geometric concurrency and strain patterns. Strains generated in a double-leg stance configuration were compared to experimental strain gauge data generated from the same target cadaver pelvis. CT landmark-based morphing and mapping techniques were efficiently applied to create a geometrically multifaceted specimen-specific pelvic FE model, which was similar to the traditionally segmented target model and better replicated the experimental strain results (R(2)=0.873). This study has shown that mesh morphing and mapping represents an efficient validated approach for pelvic FE model generation without the need for segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.
-
Quality-Aware Estimation of Facial Landmarks in Video Sequences
DEFF Research Database (Denmark)
Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.
2015-01-01
Face alignment in video is a primitive step for facial image analysis. The accuracy of the alignment greatly depends on the quality of the face image in the video frames and low quality faces are proven to cause erroneous alignment. Thus, this paper proposes a system for quality aware face...... for facial landmark detection. If the face quality is low the proposed system corrects the facial landmarks that are detected by SDM. Depending upon the face velocity in consecutive video frames and face quality measure, two algorithms are proposed for correction of landmarks in low quality faces by using...
-
Information Theory for Gabor Feature Selection for Face Recognition
Directory of Open Access Journals (Sweden)
Shen Linlin
2006-01-01
Full Text Available A discriminative and robust feature—kernel enhanced informative Gabor feature—is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and nonredundant Gabor features, which are then further enhanced by kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004, our methods demonstrate a clear advantage over existing methods in accuracy, computation efficiency, and memory cost. The proposed method has been fully tested on the FERET database using the FERET evaluation protocol. Significant improvements on three of the test data sets are observed. Compared with the classical Gabor wavelet-based approaches using a huge number of features, our method requires less than 4 milliseconds to retrieve a few hundreds of features. Due to the substantially reduced feature dimension, only 4 seconds are required to recognize 200 face images. The paper also unified different Gabor filter definitions and proposed a training sample generation algorithm to reduce the effects caused by unbalanced number of samples available in different classes.
-
Information Theory for Gabor Feature Selection for Face Recognition
Shen, Linlin; Bai, Li
2006-12-01
A discriminative and robust feature—kernel enhanced informative Gabor feature—is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and nonredundant Gabor features, which are then further enhanced by kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004), our methods demonstrate a clear advantage over existing methods in accuracy, computation efficiency, and memory cost. The proposed method has been fully tested on the FERET database using the FERET evaluation protocol. Significant improvements on three of the test data sets are observed. Compared with the classical Gabor wavelet-based approaches using a huge number of features, our method requires less than 4 milliseconds to retrieve a few hundreds of features. Due to the substantially reduced feature dimension, only 4 seconds are required to recognize 200 face images. The paper also unified different Gabor filter definitions and proposed a training sample generation algorithm to reduce the effects caused by unbalanced number of samples available in different classes.
-
The reliability of tablet computers in depicting maxillofacial radiographic landmarks
Energy Technology Data Exchange (ETDEWEB)
Tadinada, Aditya; Mahdian, Mina; Sheth, Sonam; Chandhoke, Taranpreet K.; Gopalakrishna, Aadarsh; Potluri, Anitha; Yadav, Sumit [University of Connecticut School of Dental Medicine, Farmington (United States)
2015-09-15
This study was performed to evaluate the reliability of the identification of anatomical landmarks in panoramic and lateral cephalometric radiographs on a standard medical grade picture archiving communication system (PACS) monitor and a tablet computer (iPad 5). A total of 1000 radiographs, including 500 panoramic and 500 lateral cephalometric radiographs, were retrieved from the de-identified dataset of the archive of the Section of Oral and Maxillofacial Radiology of the University Of Connecticut School Of Dental Medicine. Major radiographic anatomical landmarks were independently reviewed by two examiners on both displays. The examiners initially reviewed ten panoramic and ten lateral cephalometric radiographs using each imaging system, in order to verify interoperator agreement in landmark identification. The images were scored on a four-point scale reflecting the diagnostic image quality and exposure level of the images. Statistical analysis showed no significant difference between the two displays regarding the visibility and clarity of the landmarks in either the panoramic or cephalometric radiographs. Tablet computers can reliably show anatomical landmarks in panoramic and lateral cephalometric radiographs.
-
Accuracy of intraoral digital impressions using an artificial landmark.
Kim, Jong-Eun; Amelya, Ami; Shin, Yooseok; Shim, June-Sung
2017-06-01
Intraoral scanners have been reported to have limited accuracy in edentulous areas. Large amounts of mobile tissue and the lack of obvious anatomic landmarks make it difficult to acquire a precise digital impression of an edentulous area with an intraoral scanner. The purpose of this in vitro study was to determine the effect of an artificial landmark on a long edentulous space on the accuracy outcomes of intraoral digital impressions. A mandibular model containing 4 prepared teeth and an edentulous space of 26 mm in length was used. A blue-light light-emitting diode tabletop scanner was used as a control scanner, and 3 intraoral scanners were used as experimental groups. Five scans were made using each intraoral scanner without an artificial landmark, and another 5 scans were performed after application of an artificial landmark (a 4×3 mm alumina material) on the edentulous area. The obtained datasets were used to evaluate trueness and precision. Without an artificial landmark on the edentulous area, the mean trueness for the intraoral scanner ranged from 36.1 to 38.8 μm and the mean precision ranged from 13.0 to 43.6 μm. With an artificial landmark on the edentulous area, accuracy was improved significantly: the mean trueness was 26.7 to 31.8 μm, and the mean precision was 9.2 to 12.4 μm. The use of an alumina artificial landmark in an edentulous space improved the trueness and precision of the intraoral scanners tested. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.
-
Continuous Indoor Positioning Fusing WiFi, Smartphone Sensors and Landmarks
Directory of Open Access Journals (Sweden)
Zhi-An Deng
2016-09-01
Full Text Available To exploit the complementary strengths of WiFi positioning, pedestrian dead reckoning (PDR, and landmarks, we propose a novel fusion approach based on an extended Kalman filter (EKF. For WiFi positioning, unlike previous fusion approaches setting measurement noise parameters empirically, we deploy a kernel density estimation-based model to adaptively measure the related measurement noise statistics. Furthermore, a trusted area of WiFi positioning defined by fusion results of previous step and WiFi signal outlier detection are exploited to reduce computational cost and improve WiFi positioning accuracy. For PDR, we integrate a gyroscope, an accelerometer, and a magnetometer to determine the user heading based on another EKF model. To reduce accumulation error of PDR and enable continuous indoor positioning, not only the positioning results but also the heading estimations are recalibrated by indoor landmarks. Experimental results in a realistic indoor environment show that the proposed fusion approach achieves substantial positioning accuracy improvement than individual positioning approaches including PDR and WiFi positioning.
-
Sneve, Markus H; Sreenivasan, Kartik K; Alnæs, Dag; Endestad, Tor; Magnussen, Svein
2015-01-01
Retention of features in visual short-term memory (VSTM) involves maintenance of sensory traces in early visual cortex. However, the mechanism through which this is accomplished is not known. Here, we formulate specific hypotheses derived from studies on feature-based attention to test the prediction that visual cortex is recruited by attentional mechanisms during VSTM of low-level features. Functional magnetic resonance imaging (fMRI) of human visual areas revealed that neural populations coding for task-irrelevant feature information are suppressed during maintenance of detailed spatial frequency memory representations. The narrow spectral extent of this suppression agrees well with known effects of feature-based attention. Additionally, analyses of effective connectivity during maintenance between retinotopic areas in visual cortex show that the observed highlighting of task-relevant parts of the feature spectrum originates in V4, a visual area strongly connected with higher-level control regions and known to convey top-down influence to earlier visual areas during attentional tasks. In line with this property of V4 during attentional operations, we demonstrate that modulations of earlier visual areas during memory maintenance have behavioral consequences, and that these modulations are a result of influences from V4. Copyright © 2014 Elsevier Ltd. All rights reserved.
-
International Nuclear Information System (INIS)
Soufi, M; Arimura, H; Toyofuku, F; Nakamura, K; Hirose, T; Umezu, Y; Shioyama, Y
2016-01-01
Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed
-
Energy Technology Data Exchange (ETDEWEB)
Soufi, M; Arimura, H; Toyofuku, F [Kyushu University, Fukuoka, Fukuoka (Japan); Nakamura, K [Hamamatsu University School of Medicine, Hamamatsu, Shizuoka (Japan); Hirose, T; Umezu, Y [Kyushu University Hospital, Fukuoka, Fukuoka (Japan); Shioyama, Y [Saga Heavy Ion Medical Accelerator in Tosu, Tosu, Saga (Japan)
2016-06-15
Purpose: To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared-ray based range images by using differential geometry (curvature) features. Methods: The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non-uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray-based time-of-flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus). Results: The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001). Conclusion: Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed
-
von Cramon-Taubadel, Noreen; Frazier, Brenda C; Lahr, Marta Mirazón
2007-09-01
Geometric morphometric methods rely on the accurate identification and quantification of landmarks on biological specimens. As in any empirical analysis, the assessment of inter- and intra-observer error is desirable. A review of methods currently being employed to assess measurement error in geometric morphometrics was conducted and three general approaches to the problem were identified. One such approach employs Generalized Procrustes Analysis to superimpose repeatedly digitized landmark configurations, thereby establishing whether repeat measures fall within an acceptable range of variation. The potential problem of this error assessment method (the "Pinocchio effect") is demonstrated and its effect on error studies discussed. An alternative approach involves employing Euclidean distances between the configuration centroid and repeat measures of a landmark to assess the relative repeatability of individual landmarks. This method is also potentially problematic as the inherent geometric properties of the specimen can result in misleading estimates of measurement error. A third approach involved the repeated digitization of landmarks with the specimen held in a constant orientation to assess individual landmark precision. This latter approach is an ideal method for assessing individual landmark precision, but is restrictive in that it does not allow for the incorporation of instrumentally defined or Type III landmarks. Hence, a revised method for assessing landmark error is proposed and described with the aid of worked empirical examples. (c) 2007 Wiley-Liss, Inc.
-
Landmark navigation and autonomous landing approach with obstacle detection for aircraft
Fuerst, Simon; Werner, Stefan; Dickmanns, Dirk; Dickmanns, Ernst D.
1997-06-01
A machine perception system for aircraft and helicopters using multiple sensor data for state estimation is presented. By combining conventional aircraft sensor like gyros, accelerometers, artificial horizon, aerodynamic measuring devices and GPS with vision data taken by conventional CCD-cameras mounted on a pan and tilt platform, the position of the craft can be determined as well as the relative position to runways and natural landmarks. The vision data of natural landmarks are used to improve position estimates during autonomous missions. A built-in landmark management module decides which landmark should be focused on by the vision system, depending on the distance to the landmark and the aspect conditions. More complex landmarks like runways are modeled with different levels of detail that are activated dependent on range. A supervisor process compares vision data and GPS data to detect mistracking of the vision system e.g. due to poor visibility and tries to reinitialize the vision system or to set focus on another landmark available. During landing approach obstacles like trucks and airplanes can be detected on the runway. The system has been tested in real-time within a hardware-in-the-loop simulation. Simulated aircraft measurements corrupted by noise and other characteristic sensor errors have been fed into the machine perception system; the image processing module for relative state estimation was driven by computer generated imagery. Results from real-time simulation runs are given.
-
Directory of Open Access Journals (Sweden)
Thomas Frigeri
2014-10-01
Full Text Available Objective To establish preoperatively the localization of the cortical projection of the inferior choroidal point (ICP and use it as a reliable landmark when approaching the temporal horn through a middle temporal gyrus access. To review relevant anatomical features regarding selective amigdalohippocampectomy (AH for treatment of mesial temporal lobe epilepsy (MTLE. Method The cortical projection of the inferior choroidal point was used in more than 300 surgeries by one authors as a reliable landmark to reach the temporal horn. In the laboratory, forty cerebral hemispheres were examined. Conclusion The cortical projection of the ICP is a reliable landmark for reaching the temporal horn.
-
Face landmark point tracking using LK pyramid optical flow
Zhang, Gang; Tang, Sikan; Li, Jiaquan
2018-04-01
LK pyramid optical flow is an effective method to implement object tracking in a video. It is used for face landmark point tracking in a video in the paper. The landmark points, i.e. outer corner of left eye, inner corner of left eye, inner corner of right eye, outer corner of right eye, tip of a nose, left corner of mouth, right corner of mouth, are considered. It is in the first frame that the landmark points are marked by hand. For subsequent frames, performance of tracking is analyzed. Two kinds of conditions are considered, i.e. single factors such as normalized case, pose variation and slowly moving, expression variation, illumination variation, occlusion, front face and rapidly moving, pose face and rapidly moving, and combination of the factors such as pose and illumination variation, pose and expression variation, pose variation and occlusion, illumination and expression variation, expression variation and occlusion. Global measures and local ones are introduced to evaluate performance of tracking under different factors or combination of the factors. The global measures contain the number of images aligned successfully, average alignment error, the number of images aligned before failure, and the local ones contain the number of images aligned successfully for components of a face, average alignment error for the components. To testify performance of tracking for face landmark points under different cases, tests are carried out for image sequences gathered by us. Results show that the LK pyramid optical flow method can implement face landmark point tracking under normalized case, expression variation, illumination variation which does not affect facial details, pose variation, and that different factors or combination of the factors have different effect on performance of alignment for different landmark points.
-
Peetz, Johanna; Wilson, Anne E
2013-02-01
Much as physical landmarks help structure our representation of space, temporal landmarks such as birthdays and significant calendar dates structure our perception of time, such that people may organize or categorize their lives into "chunks" separated by these markers. Categories on the temporal landscape may vary depending on what landmarks are salient at a given time. We suggest these landmarks have implications for identity and motivation. The present research examined consequences of salient temporal landmarks for perceptions of the self across time and motivation to pursue successful future selves. Studies 1 and 2 show that temporally extended selves are perceived as less connected to, and more dissimilar from, the current self when an intervening landmark event has been made salient. Study 3 addresses the proposed mechanism, demonstrating that intervening landmarks lead people to categorize pre- and postlandmark selves into separate categories more often than when the same time period contains no salient landmarks. Finally, we examined whether landmark-induced mental contrasting of present state and future desired state could increase goal-pursuit motivation (in an effort to bridge the gap between inferior present and better future states). Studies 4-6 demonstrate that landmark-induced discrepancies between current health and hoped-for future health increased participants' motivation to exercise and increased the likelihood that they acted in line with their future-oriented goals. (c) 2013 APA, all rights reserved.
-
Discovering highly informative feature set over high dimensions
Zhang, Chongsheng; Masseglia, Florent; Zhang, Xiangliang
2012-01-01
For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.
-
Discovering highly informative feature set over high dimensions
Zhang, Chongsheng
2012-11-01
For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.
-
SIFT based algorithm for point feature tracking
Directory of Open Access Journals (Sweden)
Adrian BURLACU
2007-12-01
Full Text Available In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighborhood. Using an algorithm based on minimizing the distance between two descriptors tracking point features throughout image sequences is engaged. Experimental results, obtained from image sequences that capture scaling of different geometrical type object, reveal the performances of the tracking algorithm.
-
Chromatic Information and Feature Detection in Fast Visual Analysis.
Directory of Open Access Journals (Sweden)
Maria M Del Viva
Full Text Available The visual system is able to recognize a scene based on a sketch made of very simple features. This ability is likely crucial for survival, when fast image recognition is necessary, and it is believed that a primal sketch is extracted very early in the visual processing. Such highly simplified representations can be sufficient for accurate object discrimination, but an open question is the role played by color in this process. Rich color information is available in natural scenes, yet artist's sketches are usually monochromatic; and, black-and-white movies provide compelling representations of real world scenes. Also, the contrast sensitivity of color is low at fine spatial scales. We approach the question from the perspective of optimal information processing by a system endowed with limited computational resources. We show that when such limitations are taken into account, the intrinsic statistical properties of natural scenes imply that the most effective strategy is to ignore fine-scale color features and devote most of the bandwidth to gray-scale information. We find confirmation of these information-based predictions from psychophysics measurements of fast-viewing discrimination of natural scenes. We conclude that the lack of colored features in our visual representation, and our overall low sensitivity to high-frequency color components, are a consequence of an adaptation process, optimizing the size and power consumption of our brain for the visual world we live in.
-
Lu, Xiaoguang; Xue, Hui; Jolly, Marie-Pierre; Guetter, Christoph; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew; Zuehlsdorff, Sven; Littmann, Arne; Georgescu, Bogdan; Guehring, Jens
2011-03-01
Cardiac perfusion magnetic resonance imaging (MRI) has proven clinical significance in diagnosis of heart diseases. However, analysis of perfusion data is time-consuming, where automatic detection of anatomic landmarks and key-frames from perfusion MR sequences is helpful for anchoring structures and functional analysis of the heart, leading toward fully automated perfusion analysis. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, i.e., context. Conventional 2D approaches take into account spatial context only. Temporal signals in perfusion data present a strong cue for anchoring. We propose a joint context model to encode both spatial and temporal evidence. In addition, our spatial context is constructed not only based on the landmark of interest, but also the landmarks that are correlated in the neighboring anatomies. A discriminative model is learned through a probabilistic boosting tree. A marginal space learning strategy is applied to efficiently learn and search in a high dimensional parameter space. A fully automatic system is developed to simultaneously detect anatomic landmarks and key frames in both RV and LV from perfusion sequences. The proposed approach was evaluated on a database of 373 cardiac perfusion MRI sequences from 77 patients. Experimental results of a 4-fold cross validation show superior landmark detection accuracies of the proposed joint spatial-temporal approach to the 2D approach that is based on spatial context only. The key-frame identification results are promising.
-
Microdevelopment of Complex Featural and Spatial Integration with Contextual Support
Directory of Open Access Journals (Sweden)
Pamela L. Hirsch
2015-01-01
Full Text Available Complex spatial decisions involve the ability to combine featural and spatial information in a scene. In the present work, 4- through 9-year-old children completed a complex map-scene correspondence task under baseline and supported conditions. Children compared a photographed scene with a correct map and with map-foils that made salient an object feature or spatial property. Map-scene matches were analyzed for the effects of age and featural-spatial information on children’s selections. In both conditions children significantly favored maps that highlighted object detail and object perspective rather than color, landmark, and metric elements. Children’s correct performance did not differ by age and was suboptimal, but their ability to choose correct maps improved significantly when contextual support was provided. Strategy variability was prominent for all age groups, but at age 9 with support children were more likely to give up their focus on features and transition to the use of spatial strategies. These findings suggest the possibility of a U-shaped curve for children’s development of geometric knowledge: geometric coding is predominant early on, diminishes for a time in middle childhood in favor of a preference for features, and then reemerges along with the more advanced abilities to combine featural and spatial information.
-
3D facial landmarks: Inter-operator variability of manual annotation
DEFF Research Database (Denmark)
Fagertun, Jens; Harder, Stine; Rosengren, Anders
2014-01-01
Background Manual annotation of landmarks is a known source of variance, which exist in all fields of medical imaging, influencing the accuracy and interpretation of the results. However, the variability of human facial landmarks is only sparsely addressed in the current literature as opposed to ...
-
Friberg, Anders; Schoonderwaldt, Erwin; Hedblad, Anton; Fabiani, Marco; Elowsson, Anders
2014-10-01
The notion of perceptual features is introduced for describing general music properties based on human perception. This is an attempt at rethinking the concept of features, aiming to approach the underlying human perception mechanisms. Instead of using concepts from music theory such as tones, pitches, and chords, a set of nine features describing overall properties of the music was selected. They were chosen from qualitative measures used in psychology studies and motivated from an ecological approach. The perceptual features were rated in two listening experiments using two different data sets. They were modeled both from symbolic and audio data using different sets of computational features. Ratings of emotional expression were predicted using the perceptual features. The results indicate that (1) at least some of the perceptual features are reliable estimates; (2) emotion ratings could be predicted by a small combination of perceptual features with an explained variance from 75% to 93% for the emotional dimensions activity and valence; (3) the perceptual features could only to a limited extent be modeled using existing audio features. Results clearly indicated that a small number of dedicated features were superior to a "brute force" model using a large number of general audio features.
-
Virtual skeletal complex model- and landmark-guided orthognathic surgery system.
Lee, Sang-Jeong; Woo, Sang-Yoon; Huh, Kyung-Hoe; Lee, Sam-Sun; Heo, Min-Suk; Choi, Soon-Chul; Han, Jeong Joon; Yang, Hoon Joo; Hwang, Soon Jung; Yi, Won-Jin
2016-05-01
In this study, correction of the maxillofacial deformities was performed by repositioning bone segments to an appropriate location according to the preoperative planning in orthognathic surgery. The surgery was planned using the patient's virtual skeletal models fused with optically scanned three-dimensional dentition. The virtual maxillomandibular complex (MMC) model of the patient's final occlusal relationship was generated by fusion of the maxillary and mandibular models with scanned occlusion. The final position of the MMC was simulated preoperatively by planning and was used as a goal model for guidance. During surgery, the intraoperative registration was finished immediately using only software processing. For accurate repositioning, the intraoperative MMC model was visualized on the monitor with respect to the simulated MMC model, and the intraoperative positions of multiple landmarks were also visualized on the MMC surface model. The deviation errors between the intraoperative and the final positions of each landmark were visualized quantitatively. As a result, the surgeon could easily recognize the three-dimensional deviation of the intraoperative MMC state from the final goal model without manually applying a pointing tool, and could also quickly determine the amount and direction of further MMC movements needed to reach the goal position. The surgeon could also perform various osteotomies and remove bone interference conveniently, as the maxillary tracking tool could be separated from the MMC. The root mean square (RMS) difference between the preoperative planning and the intraoperative guidance was 1.16 ± 0.34 mm immediately after repositioning. After surgery, the RMS differences between the planning and the postoperative computed tomographic model were 1.31 ± 0.28 mm and 1.74 ± 0.73 mm for the maxillary and mandibular landmarks, respectively. Our method provides accurate and flexible guidance for bimaxillary orthognathic surgery based on
-
Semi-Automatic Anatomical Tree Matching for Landmark-Based Elastic Registration of Liver Volumes
Directory of Open Access Journals (Sweden)
Klaus Drechsler
2010-01-01
Full Text Available One promising approach to register liver volume acquisitions is based on the branching points of the vessel trees as anatomical landmarks inherently available in the liver. Automated tree matching algorithms were proposed to automatically find pair-wise correspondences between two vessel trees. However, to the best of our knowledge, none of the existing automatic methods are completely error free. After a review of current literature and methodologies on the topic, we propose an efficient interaction method that can be employed to support tree matching algorithms with important pre-selected correspondences or after an automatic matching to manually correct wrongly matched nodes. We used this method in combination with a promising automatic tree matching algorithm also presented in this work. The proposed method was evaluated by 4 participants and a CT dataset that we used to derive multiple artificial datasets.
-
Hubbert, Beth
2009-01-01
For the author, it all began with a summer trip to London and Paris. Inspired by the art and architecture of London and Paris, she was determined to bring her experience back home to her students. To do this, she organized a lesson in world landmarks focusing on structures of importance that fit into three categories: relevance to the world,…
-
Chen, Yifei; Sun, Yuxing; Han, Bing-Qing
2015-01-01
Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.
-
Identification of informative features for predicting proinflammatory potentials of engine exhausts.
Wang, Chia-Chi; Lin, Ying-Chi; Lin, Yuan-Chung; Jhang, Syu-Ruei; Tung, Chun-Wei
2017-08-18
The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment. To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm. A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively. The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.
-
Audiovisual laughter detection based on temporal features
Petridis, Stavros; Nijholt, Antinus; Nijholt, A.; Pantic, M.; Pantic, Maja; Poel, Mannes; Poel, M.; Hondorp, G.H.W.
2008-01-01
Previous research on automatic laughter detection has mainly been focused on audio-based detection. In this study we present an audiovisual approach to distinguishing laughter from speech based on temporal features and we show that the integration of audio and visual information leads to improved
-
Competition between landmarks in spatial learning: the role of proximity to the goal.
Chamizo, V D; Manteiga, R D; Rodrigo, T; Mackintosh, N J
2006-01-10
In two experiments, rats were trained to find a hidden platform in a Morris pool in the presence of two landmarks. Landmark B was present on all training trials, on half the trials accompanied by landmark A, on the remainder by landmark C. For rats in Group Bn, B was near the location of the platform; for those in Group Bf, B was far from the platform. Group Bn performed better than Group Bf on test trials to B alone, but significantly worse on test trials to a new configuration formed by A and C. Thus, the spatial proximity of B to the platform affected not only how well it could be used to locate the platform, but also its ability to prevent learning about other landmarks.
-
Effects of image enhancement on reliability of landmark identification in digital cephalometry
Directory of Open Access Journals (Sweden)
M Oshagh
2013-01-01
Full Text Available Introduction: Although digital cephalometric radiography is gaining popularity in orthodontic practice, the most important source of error in its tracing is uncertainty in landmark identification. Therefore, efforts to improve accuracy in landmark identification were directed primarily toward the improvement in image quality. One of the more useful techniques of this process involves digital image enhancement which can increase overall visual quality of image, but this does not necessarily mean a better identification of landmarks. The purpose of this study was to evaluate the effectiveness of digital image enhancements on reliability of landmark identification. Materials and Methods: Fifteen common landmarks including 10 skeletal and 5 soft tissues were selected on the cephalograms of 20 randomly selected patients, prepared in Natural Head Position (NHP. Two observers (orthodontists identified landmarks on the 20 original photostimulable phosphor (PSP digital cephalogram images and 20 enhanced digital images twice with an intervening time interval of at least 4 weeks. The x and y coordinates were further analyzed to evaluate the pattern of recording differences in horizontal and vertical directions. Reliability of landmarks identification was analyzed by paired t test. Results: There was a significant difference between original and enhanced digital images in terms of reliability of points Ar and N in vertical and horizontal dimensions, and enhanced images were significantly more reliable than original images. Identification of A point, Pogonion and Pronasal points, in vertical dimension of enhanced images was significantly more reliable than original ones. Reliability of Menton point identification in horizontal dimension was significantly more in enhanced images than original ones. Conclusion: Direct digital image enhancement by altering brightness and contrast can increase reliability of some landmark identification and this may lead to more
-
Digital analysis of facial landmarks in determining facial midline among Punjabi population
Directory of Open Access Journals (Sweden)
Nirmal Kurian
2018-01-01
Full Text Available Introduction: Prosthodontic rehabilitation aims to achieve the best possible facial esthetic appearance for a patient. Attaining facial symmetry forms the basic element for esthetics, and knowledge of the midline of face will result in a better understanding of dentofacial esthetics. Currently, there are no guidelines that direct the choice of specific anatomic landmarks to determine the midline of the face or mouth. Most clinicians choose one specific anatomic landmark and an imaginary line passing through it. Thus, the clinician is left with no established guidelines to determine facial midline. Objective: The purpose of the study is to digitally determine the relationship of facial landmarks with midline of face and formulate a guideline for choosing anatomic landmark among Punjabi population. Materials and Methods: Three commonly used anatomic landmarks, namely nasion, tip of the nose, and tip of the philtrum, were marked clinically on 100 participants (age range: 21–45 years. Frontal full-face digital images of the participants in smile were then made under standardized conditions. Midline analysis was carried out digitally using an image analyzing software. The entire process of midline analysis was done by a single observer and repeated twice. Reliability analysis and one-sample t-tests were conducted. Results: The results indicated that each of the four landmarks deviated uniquely and significantly (P < 0.001 from the midlines of the face as well as the mouth. Conclusions: Within the limitations of the study, the hierarchy of anatomic landmarks closest to the midline of the face in smile was as follows: (1 Intercommissural midlines, (2 Tip of philtrum, (3 Nasion, (4 Tip of the nose, and (5 Dental midlines. The hierarchy of anatomical landmarks closest to the intercommissural/mouth midline was: (1 Tip of philtrum, (2 Tip of the nose, (3 Nasion, and (4 dental midline.
-
Directory of Open Access Journals (Sweden)
V. K. Hohlov
2017-01-01
Full Text Available The article forms the rationale for selecting the informative features of the helicopter and aircraft acoustic signals to solve a problem of their recognition and shows that the most informative ones are the counts of extrema in the energy spectra of the input signals, which represent non-centered random variables. An apparatus of the multiple initial regression coefficients was selected as a mathematical tool of research. The application of digital re-circulators with positive and negative feedbacks, which have the comb-like frequency characteristics, solves the problem of selecting informative features. A distinguishing feature of such an approach is easy agility of the comb frequency characteristics just through the agility of a delay value of digital signal in the feedback circuit. Adding an adaptation block to the selection block of the informative features enables us to ensure the invariance of used informative feature and counts of local extrema of the spectral power density to the airspeed of a helicopter. The paper gives reasons for the principle of adaptation and the structure of the adaptation block. To form the discriminator characteristics are used the cross-correlation statistical characteristics of the quadrature components of acoustic signal realizations, obtained by Hilbert transform. The paper proposes to provide signal recognition using a regression algorithm that allows handling the non-centered informative features and using a priori information about coefficients of initial regression of signal and noise.The simulation in Matlab Simulink has shown that selected informative features of signals in regressive processing of signal realizations of 0.5 s duration have good separability, and based on a set of 100 acoustic signal realizations in each class in full-scale conditions, has proved ensuring a correct recognition probability of 0.975, at least. The considered principles of informative features selection and adaptation can
-
Information Processing Features Can Detect Behavioral Regimes of Dynamical Systems
Directory of Open Access Journals (Sweden)
Rick Quax
2018-01-01
Full Text Available In dynamical systems, local interactions between dynamical units generate correlations which are stored and transmitted throughout the system, generating the macroscopic behavior. However a framework to quantify exactly how these correlations are stored, transmitted, and combined at the microscopic scale is missing. Here we propose to characterize the notion of “information processing” based on all possible Shannon mutual information quantities between a future state and all possible sets of initial states. We apply it to the 256 elementary cellular automata (ECA, which are the simplest possible dynamical systems exhibiting behaviors ranging from simple to complex. Our main finding is that only a few information features are needed for full predictability of the systemic behavior and that the “information synergy” feature is always most predictive. Finally we apply the idea to foreign exchange (FX and interest-rate swap (IRS time-series data. We find an effective “slowing down” leading indicator in all three markets for the 2008 financial crisis when applied to the information features, as opposed to using the data itself directly. Our work suggests that the proposed characterization of the local information processing of units may be a promising direction for predicting emergent systemic behaviors.
-
Histological image classification using biologically interpretable shape-based features
International Nuclear Information System (INIS)
Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D
2013-01-01
Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions
-
Directory of Open Access Journals (Sweden)
Ling-li Jiang
2014-01-01
Full Text Available Multisensor information fusion, when applied to fault diagnosis, the time-space scope, and the quantity of information are expanded compared to what could be acquired by a single sensor, so the diagnostic object can be described more comprehensively. This paper presents a methodology of fault diagnosis in rotating machinery using multisensor information fusion that all the features are calculated using vibration data in time domain to constitute fusional vector and the support vector machine (SVM is used for classification. The effectiveness of the presented methodology is tested by three case studies: diagnostic of faulty gear, rolling bearing, and identification of rotor crack. For each case study, the sensibilities of the features are analyzed. The results indicate that the peak factor is the most sensitive feature in the twelve time-domain features for identifying gear defect, and the mean, amplitude square, root mean square, root amplitude, and standard deviation are all sensitive for identifying gear, rolling bearing, and rotor crack defect comparatively.
-
Influence of Landmarks on Spatial Memory in Short-nosed Fruit Bat, Cynopterus sphinx.
Zeng, Yu; Zhang, Xin-Wen; Zhu, Guang-Jian; Gong, Yan-Yan; Yang, Jian; Zhang, Li-Biao
2010-04-01
In order to study the relationship between landmarks and spatial memory in short-nosed fruit bat, Cynopterus sphinx (Megachiroptera, Pteropodidae), we simulated a foraging environment in the laboratory. Different landmarks were placed to gauge the spatial memory of C. sphinx. We changed the number of landmarks every day with 0 landmarks again on the fifth day (from 0, 2, 4, 8 to 0). Individuals from the control group were exposed to the identical artificial foraging environment, but without landmarks. The results indicated that there was significant correlation between the time of the first foraging and the experimental days in both groups (Pearson Correlation: experimental group: r=-0.593, P0.05), but there was significant correlation between the success rates of foraging and the experimental days in the control groups (Pearson Correlation: r=0.445, P0.05); also, there was no significant difference in success rates of foraging between these two groups (GLM: F(0.05,1 )=0.849, P>0.05). The results of our experiment suggest that spatial memory in C. sphinx was formed gradually and that the placed landmarks appeared to have no discernable effects on the memory of the foraging space.
-
Directory of Open Access Journals (Sweden)
Wu Xing
2014-03-01
Full Text Available Vision recognition and RFID perception are used to develop a smart AGV travelling on fixed paths while retaining low-cost, simplicity and reliability. Visible landmarks can describe features of shapes and geometric dimensions of lines and intersections, and RFID tags can directly record global locations on pathways and the local topological relations of crossroads. A topological map is convenient for building and editing without the need for accurate poses when establishing a priori knowledge of a workplace. To obtain the flexibility of bidirectional movement along guide-paths, a camera placed in the centre of the AGV looks downward vertically at landmarks on the floor. A small visual field presents many difficulties for vision guidance, especially for real-time, correct and reliable recognition of multi-branch crossroads. First, the region projection and contour scanning methods are both used to extract the features of shapes. Then LDA is used to reduce the number of the features' dimensions. Third, a hierarchical SVM classifier is proposed to classify their multi-branch patterns once the features of the shapes are complete. Our experiments in landmark recognition and navigation show that low-cost vision systems are insusceptible to visual noises, image breakages and floor changes, and a vision-based AGV can locate itself precisely on its paths, recognize different crossroads intelligently by verifying the conformance of vision and RFID information, and select its next pathway efficiently in a bidirectional flow network.
-
Feature Selection Based on Mutual Correlation
Czech Academy of Sciences Publication Activity Database
Haindl, Michal; Somol, Petr; Ververidis, D.; Kotropoulos, C.
2006-01-01
Roč. 19, č. 4225 (2006), s. 569-577 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection Subject RIV: BD - Theory of Information Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/haindl-feature selection based on mutual correlation.pdf
-
Collaborative Filtering Fusing Label Features Based on SDAE
DEFF Research Database (Denmark)
Huo, Huan; Liu, Xiufeng; Zheng, Deyuan
2017-01-01
problem, auxiliary information such as labels are utilized. Another approach of recommendation system is content-based model which can’t be directly integrated with CF-based model due to its inherent characteristics. Considering that deep learning algorithms are capable of extracting deep latent features......, this paper applies Stack Denoising Auto Encoder (SDAE) to content-based model and proposes LCF(Deep Learning for Collaborative Filtering) algorithm by combing CF-based model which fuses label features. Experiments on real-world data sets show that DLCF can largely overcome the sparsity problem...... and significantly improves the state of art approaches....
-
Digital video steganalysis using motion vector recovery-based features.
Deng, Yu; Wu, Yunjie; Zhou, Linna
2012-07-10
As a novel digital video steganography, the motion vector (MV)-based steganographic algorithm leverages the MVs as the information carriers to hide the secret messages. The existing steganalyzers based on the statistical characteristics of the spatial/frequency coefficients of the video frames cannot attack the MV-based steganography. In order to detect the presence of information hidden in the MVs of video streams, we design a novel MV recovery algorithm and propose the calibration distance histogram-based statistical features for steganalysis. The support vector machine (SVM) is trained with the proposed features and used as the steganalyzer. Experimental results demonstrate that the proposed steganalyzer can effectively detect the presence of hidden messages and outperform others by the significant improvements in detection accuracy even with low embedding rates.
-
Borstlap, Waa; Deijen, C. L.; den Dulk, M.; Bonjer, H. J.; van de Velde, C. J.; Bemelman, W. A.; Tanis, P. J.; Aalbers, A.; Acherman, Y.; Algie, G. D.; Alting von Geusau, B.; Amelung, F.; Aukema, T. S.; Bakker, I. S.; Basha, S.; Bastiaansen, A. J. N. M.; Belgers, E.; Bleeker, W.; Blok, J.; Bosker, R. J. I.; Bosmans, J. W.; Boute, M. C.; Bouvy, N. D.; Bouwman, H.; Brandt-Kerkhof, A.; Brinkman, D. J.; Bruin, S.; Bruns, E. R. J.; Burbach, J. P. M.; Burger, J. W. A.; Buskens, C. J.; Clermonts, S.; Coenen, P. P. L. O.; Compaan, C.; Consten, E. C. J.; Darbyshire, T.; de Mik, S. M. L.; de Graaf, E. J. R.; de Groot, I.; de Vos Tot Nederveen Cappel, R. J. L.; de Wilt, J. H. W.; van der Wolde, J.; den Boer, F. C.; Dekker, J. W. T.; Demirkiran, A.; van Duijvendijk, P.; Musters, G. D.; van Rossem, C. C.; Schreuder, A. M.; Swank, H. A.
2017-01-01
Aim A Snapshot study design eliminates changes in treatment and outcome over time. This population based Snapshot study aimed to determine current practice and outcome of rectal cancer treatment with published landmark randomized controlled trials as a benchmark. Method In this collaborative
-
Borstlap, W. A. A.; Deijen, C. L.; den Dulk, M.; Bonjer, H. J.; van de Velde, C. J.; Bemelman, W. A.; Tanis, P. J.; Aalbers, A.; Acherman, Y.; Algie, G. D.; von Geu-sau, B. Alting; Amelung, F.; Aukema, T. S.; Bakker, I. S.; Bartels, S. A.; Basha, S.; Bastiaansen, A. J. N. M.; Belgers, E.; Bleeker, W.; Blok, J.; Bosker, R. J. I.; Bosmans, J. W.; Boute, M. C.; Bouvy, N. D.; Bouwman, H.; Brandt-Kerkhof, A.; Brinkman, D. J.; Bruin, S.; Bruns, E. R. J.; Burbach, J. P. M.; Burger, J. W. A.; Buskens, C. J.; Clermonts, S.; Coene, P. P. L. O.; Compaan, C.; Consten, E. C. J.; Darbyshire, T.; de Mik, S. M. L.; de Graaf, E. J. R.; de Groot, I.; Cappel, R. J. L. de Vos Tot Nederveen; de Wilt, J. H. W.; van der Wolde, J.; den Boer, F. C.; Furnee, E. J. B.; Havenga, K.; Klaase, J.; Holzik, M. F. Lutke; Meerdink, M.; Wevers, K.
Aim A Snapshot study design eliminates changes in treatment and outcome over time. This population based Snapshot study aimed to determine current practice and outcome of rectal cancer treatment with published landmark randomized controlled trials as a benchmark. Method In this collaborative
-
Chamizo, Victoria D; Rodríguez, Clara A; Espinet, Alfredo; Mackintosh, N J
2012-07-01
When they are trained in a Morris water maze to find a hidden platform, whose location is defined by a number of equally spaced visual landmarks round the circumference of the pool, rats are equally able to find the platform when tested with any two of the landmarks (Prados, & Trobalon, 1998; Rodrigo, Chamizo, McLaren, & Mackintosh, 1997). This suggests that none of the landmarks was completely overshadowed by any of the others. In Experiment 1 one pair of groups was trained with four equally salient visual landmarks spaced at equal intervals around the edge of the pool, while a second pair was trained with two landmarks only, either relatively close to or far from the hidden platform. After extensive training, both male and female rats showed a reciprocal overshadowing effect: on a test with two landmarks only (either close to or far from the platform), rats trained with four landmarks spent less time in the platform quadrant than those trained with only two. Experiment 2 showed that animals trained with two landmarks and then tested with four also performed worse on test than those trained and tested with two landmarks only. This suggests that generalization decrement, rather than associative competition, provides a sufficient explanation for the overshadowing observed in Experiment 1. Experiment 3 provided a within-experiment replication of the results of Experiments 1 and 2. Finally, Experiment 4 showed that rats trained with a configuration of two landmarks learn their identity.
-
Della Croce, Ugo; Leardini, Alberto; Chiari, Lorenzo; Cappozzo, Aurelio
2005-02-01
Estimating the effects of different sources of error on joint kinematics is crucial for assessing the reliability of human movement analysis. The goal of the present paper is to review the different approaches dealing with joint kinematics sensitivity to rotation axes and the precision of anatomical landmark determination. Consistent with the previous papers in this series, the review is limited to studies performed with video-based stereophotogrammetric systems. Initially, studies dealing with estimates of precision in determining the location of both palpable and internal anatomical landmarks are reviewed. Next, the effects of anatomical landmark position uncertainty on anatomical frames are shown. Then, methods reported in the literature for estimating error propagation from anatomical axes location to joint kinematics are described. Interestingly, studies carried out using different approaches reported a common conclusion: when joint rotations occur mainly in a single plane, minor rotations out of this plane are strongly affected by errors introduced at the anatomical landmark identification level and are prone to misinterpretation. Finally, attempts at reducing joint kinematics errors due to anatomical landmark position uncertainty are reported. Given the relevance of this source of errors in the determination of joint kinematics, it is the authors' opinion that further efforts should be made in improving the reliability of the joint axes determination.
-
Visual Appearance-Based Unmanned Vehicle Sequential Localization
Directory of Open Access Journals (Sweden)
Wei Liu
2013-01-01
Full Text Available Localizationis of vital importance for an unmanned vehicle to drive on the road. Most of the existing algorithms are based on laser range finders, inertial equipment, artificial landmarks, distributing sensors or global positioning system(GPS information. Currently, the problem of localization with vision information is most concerned. However, vision-based localization techniquesare still unavailable for practical applications. In this paper, we present a vision-based sequential probability localization method. This method uses the surface information of the roadside to locate the vehicle, especially in the situation where GPS information is unavailable. It is composed of two step, first, in a recording stage, we construct a ground truthmap with the appearance of the roadside environment. Then in an on-line stage, we use a sequential matching approach to localize the vehicle. In the experiment, we use two independent cameras to observe the environment, one is left-orientated and the other is right. SIFT features and Daisy features are used to represent for the visual appearance of the environment. The experiment results show that the proposed method could locate the vehicle in a complicated, large environment with high reliability.
-
Morita, Yusuke; Ogihara, Naomichi; Kanai, Takashi; Suzuki, Hiromasa
2013-08-01
Three-dimensional geometric morphometric techniques have been widely used in quantitative comparisons of craniofacial morphology in humans and nonhuman primates. However, few anatomical landmarks can actually be defined on the neurocranium. In this study, an alternative method is proposed for defining semi-landmarks on neurocranial surfaces for use in detailed analysis of cranial shape. Specifically, midsagittal, nuchal, and temporal lines were approximated using Bezier curves and equally spaced points along each of the curves were defined as semi-landmarks. The shortest paths connecting pairs of anatomical landmarks as well as semi-landmarks were then calculated in order to represent the surface morphology between landmarks using equally spaced points along the paths. To evaluate the efficacy of this method, the previously outlined technique was used in morphological analysis of sexual dimorphism in modern Japanese crania. The study sample comprised 22 specimens that were used to generate 110 anatomical semi-landmarks, which were used in geometric morphometric analysis. Although variations due to sexual dimorphism in human crania are very small, differences could be identified using the proposed landmark placement, which demonstrated the efficacy of the proposed method. Copyright © 2013 Wiley Periodicals, Inc.
-
Directory of Open Access Journals (Sweden)
C. M. Gevaert
2016-06-01
Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.
-
Effect of Ultrasonography on Student Learning of Shoulder Anatomy and Landmarks.
de Vries, Kristen D; Brown, Rebecca; Mazzie, Joseph; Jung, Min-Kyung; Yao, Sheldon C; Terzella, Michael J
2018-01-01
Ultrasonography is becoming more common in clinical use, and it has been shown to have promising results when introduced into medical school curricula. To determine whether the use of ultrasonography as an educational supplement can improve osteopathic medical students' confidence and ability to locate 4 specific shoulder anatomical landmarks: the coracoid process, the transverse process of T1, the long head of the biceps within the bicipital groove, and the supraspinatus tendon. In this randomized controlled study, first-year osteopathic medical students aged 18 years or older were recruited and randomly assigned to a group with exposure (ultrasonography group) or without exposure (control group) to an ultrasonography machine. First, a survey was administered to measure students' baseline knowledge of shoulder anatomy, confidence in palpation skills, and opinion on anatomical landmark identification teaching methods. Next, students were shown presentations on shoulder anatomy and allowed to practice locating and palpating the specified landmarks. Students in the ultrasonography group were also given instruction on the use of ultrasonography. All students were asked to locate each of the 4 specified anatomical landmarks and then given a follow-up survey. A Mann Whitney U test was used to compare the confidence of the students before and after the intervention. A secondary analysis was performed to compare the degree of deviance from the correct position of the specified anatomical landmark between the ultrasonography and control groups. P values less than .05 were considered statistically significant. Sixty-four students participated. Compared with the control group, students in the ultrasonography group had a greater increase in confidence after the session in their ability to locate the coracoid process, bicipital tendon, and supraspinatus tendon (P=.022, P=.029, P=.44, respectively). Students in the ultrasonography group were also able to more accurately palpate
-
Evaluating Users' Satisfaction With Landmark University's Online ...
African Journals Online (AJOL)
OPAC) of Landmark University, Nigeria. The study adopted the descriptive survey design. The target population were 200 students, which were purposively selected to participate in the study. Questionnaire were distributed to all the purposively ...
-
Finger vein recognition based on the hyperinformation feature
Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu
2014-01-01
The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.
-
Face Alignment via Regressing Local Binary Features.
Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian
2016-03-01
This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.
-
Adaptive Feature Based Control of Compact Disk Players
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Stoustrup, Jakob; Vidal, Enrique Sanchez
2005-01-01
Many have experienced the problem that their Compact Disc players have difficulties playing Compact Discs with surface faults like scratches and fingerprints. The cause of this is due to the two servo control loops used to keep the Optical Pick-up Unit focused and radially on the information track...... of the Compact Disc. The problem is to design servo controllers which are well suited for handling surface faults which disturb the position measurement and still react sufficiently against normal disturbances like mechanical shocks. In previous work of the same authors a feature based control scheme for CD......-players playing CDs with surface fault is derived and described. This feature based control scheme uses precomputed base to remove the surface fault influence from the position measurements. In this paper an adaptive version of the feature based control scheme is proposed and described. This adaptive scheme can...
-
Interactions of visual odometry and landmark guidance during food search in honeybees
Vladusich, T; Hemmi, JM; Srinivasan, MV; Zeil, J
How do honeybees use visual odometry and goal-defining landmarks to guide food search? In one experiment, bees were trained to forage in an optic-flow-rich tunnel with a landmark positioned directly above the feeder. Subsequent food-search tests indicated that bees searched much more accurately when
-
Feature Selection for Chemical Sensor Arrays Using Mutual Information
Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.
2014-01-01
We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058
-
AUTOMATIC DETECTION AND CLASSIFICATION OF RETINAL VASCULAR LANDMARKS
Directory of Open Access Journals (Sweden)
Hadi Hamad
2014-06-01
Full Text Available The main contribution of this paper is introducing a method to distinguish between different landmarks of the retina: bifurcations and crossings. The methodology may help in differentiating between arteries and veins and is useful in identifying diseases and other special pathologies, too. The method does not need any special skills, thus it can be assimilated to an automatic way for pinpointing landmarks; moreover it gives good responses for very small vessels. A skeletonized representation, taken out from the segmented binary image (obtained through a preprocessing step, is used to identify pixels with three or more neighbors. Then, the junction points are classified into bifurcations or crossovers depending on their geometrical and topological properties such as width, direction and connectivity of the surrounding segments. The proposed approach is applied to the public-domain DRIVE and STARE datasets and compared with the state-of-the-art methods using proper validation parameters. The method was successful in identifying the majority of the landmarks; the average correctly identified bifurcations in both DRIVE and STARE datasets for the recall and precision values are: 95.4% and 87.1% respectively; also for the crossovers, the recall and precision values are: 87.6% and 90.5% respectively; thus outperforming other studies.
-
Sex differences in a landmark environmental re-orientation task only during the learning phase.
Piccardi, Laura; Bianchini, Filippo; Iasevoli, Luigi; Giannone, Gianluca; Guariglia, Cecilia
2011-10-10
Sex differences are consistently reported in human navigation. Indeed, to orient themselves during navigation women are more likely to use landmark-based strategies and men Euclidean-based strategies. The difference could be due to selective social pressure, which fosters greater spatial ability in men, or biological factors. And the great variability of the results reported in the literature could be due to the experimental setting more than real differences in ability. In this study, navigational behaviour was assessed by means of a place-learning task in which a modified version of the Morris water maze for humans was used to evaluate sex differences. In using landmarks, sex differences emerged only during the learning phase. Although the men were faster than the women in locating the target position, the differences between the sexes disappeared in delayed recall. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
-
Feature study of hysterical blindness EEG based on FastICA with combined-channel information.
Qin, Xuying; Wang, Wei; Hu, Lintao; Wang, Xu; Yuan, Xiaojie
2015-01-01
An appropriate feature study of hysteria electroencephalograms (EEG) would provide new insights into neural mechanisms of the disease, and also make improvements in patient diagnosis and management. The objective of this paper is to provide an explanation for what causes a particular visual loss, by associating the features of hysterical blindness EEG with brain function. An idea for the novel feature extraction for hysterical blindness EEG, utilizing combined-channel information, was applied in this paper. After channels had been combined, the sliding-window-FastICA was applied to process the combined normal EEG and hysteria EEG, respectively. Kurtosis features were calculated from the processed signals. As the comparison feature, the power spectral density of normal and hysteria EEG were computed. According to the feature analysis results, a region of brain dysfunction was located at the occipital lobe, O1 and O2. Furthermore, new abnormality was found at the parietal lobe, C3, C4, P3, and P4, that provided us with a new perspective for understanding hysterical blindness. Indicated by the kurtosis results which were consistent with brain function and the clinical diagnosis, our method was found to be a useful tool to capture features in hysterical blindness EEG.
-
Image mosaicking based on feature points using color-invariant values
Lee, Dong-Chang; Kwon, Oh-Seol; Ko, Kyung-Woo; Lee, Ho-Young; Ha, Yeong-Ho
2008-02-01
In the field of computer vision, image mosaicking is achieved using image features, such as textures, colors, and shapes between corresponding images, or local descriptors representing neighborhoods of feature points extracted from corresponding images. However, image mosaicking based on feature points has attracted more recent attention due to the simplicity of the geometric transformation, regardless of distortion and differences in intensity generated by camera motion in consecutive images. Yet, since most feature-point matching algorithms extract feature points using gray values, identifying corresponding points becomes difficult in the case of changing illumination and images with a similar intensity. Accordingly, to solve these problems, this paper proposes a method of image mosaicking based on feature points using color information of images. Essentially, the digital values acquired from a real digital color camera are converted to values of a virtual camera with distinct narrow bands. Values based on the surface reflectance and invariant to the chromaticity of various illuminations are then derived from the virtual camera values and defined as color-invariant values invariant to changing illuminations. The validity of these color-invariant values is verified in a test using a Macbeth Color-Checker under simulated illuminations. The test also compares the proposed method using the color-invariant values with the conventional SIFT algorithm. The accuracy of the matching between the feature points extracted using the proposed method is increased, while image mosaicking using color information is also achieved.
-
Spectral-based features ranking for gamelan instruments identification using filter techniques
Directory of Open Access Journals (Sweden)
Diah P Wulandari
2013-03-01
Full Text Available In this paper, we describe an approach of spectral-based features ranking for Javanese gamelaninstruments identification using filter techniques. The model extracted spectral-based features set of thesignal using Short Time Fourier Transform (STFT. The rank of the features was determined using the fivealgorithms; namely ReliefF, Chi-Squared, Information Gain, Gain Ratio, and Symmetric Uncertainty. Then,we tested the ranked features by cross validation using Support Vector Machine (SVM. The experimentshowed that Gain Ratio algorithm gave the best result, it yielded accuracy of 98.93%.
-
Tensor-based Multi-view Feature Selection with Applications to Brain Diseases
Cao, Bokai; He, Lifang; Kong, Xiangnan; Yu, Philip S.; Hao, Zhifeng; Ragin, Ann B.
2015-01-01
In the era of big data, we can easily access information from multiple views which may be obtained from different sources or feature subsets. Generally, different views provide complementary information for learning tasks. Thus, multi-view learning can facilitate the learning process and is prevalent in a wide range of application domains. For example, in medical science, measurements from a series of medical examinations are documented for each subject, including clinical, imaging, immunologic, serologic and cognitive measures which are obtained from multiple sources. Specifically, for brain diagnosis, we can have different quantitative analysis which can be seen as different feature subsets of a subject. It is desirable to combine all these features in an effective way for disease diagnosis. However, some measurements from less relevant medical examinations can introduce irrelevant information which can even be exaggerated after view combinations. Feature selection should therefore be incorporated in the process of multi-view learning. In this paper, we explore tensor product to bring different views together in a joint space, and present a dual method of tensor-based multi-view feature selection (dual-Tmfs) based on the idea of support vector machine recursive feature elimination. Experiments conducted on datasets derived from neurological disorder demonstrate the features selected by our proposed method yield better classification performance and are relevant to disease diagnosis. PMID:25937823
-
Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo.
Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng
2016-01-28
The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.
-
Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo
Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng
2016-01-01
The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.
-
Mutual Information Based Dynamic Integration of Multiple Feature Streams for Robust Real-Time LVCSR
Sato, Shoei; Kobayashi, Akio; Onoe, Kazuo; Homma, Shinichi; Imai, Toru; Takagi, Tohru; Kobayashi, Tetsunori
We present a novel method of integrating the likelihoods of multiple feature streams, representing different acoustic aspects, for robust speech recognition. The integration algorithm dynamically calculates a frame-wise stream weight so that a higher weight is given to a stream that is robust to a variety of noisy environments or speaking styles. Such a robust stream is expected to show discriminative ability. A conventional method proposed for the recognition of spoken digits calculates the weights front the entropy of the whole set of HMM states. This paper extends the dynamic weighting to a real-time large-vocabulary continuous speech recognition (LVCSR) system. The proposed weight is calculated in real-time from mutual information between an input stream and active HMM states in a searchs pace without an additional likelihood calculation. Furthermore, the mutual information takes the width of the search space into account by calculating the marginal entropy from the number of active states. In this paper, we integrate three features that are extracted through auditory filters by taking into account the human auditory system's ability to extract amplitude and frequency modulations. Due to this, features representing energy, amplitude drift, and resonant frequency drifts, are integrated. These features are expected to provide complementary clues for speech recognition. Speech recognition experiments on field reports and spontaneous commentary from Japanese broadcast news showed that the proposed method reduced error words by 9.2% in field reports and 4.7% in spontaneous commentaries relative to the best result obtained from a single stream.
-
Gyftopoulos, Soterios; Abballe, Valentino; Virk, Mandeep S; Koo, James; Gold, Heather T; Subhas, Naveen
2018-04-09
The purpose of this study was to determine the cost-effectiveness of landmark-based and image-guided intraarticular steroid injections for the initial treatment of a population with adhesive capsulitis. A decision analytic model from the health care system perspective over a 6-month time frame for 50-year-old patients with clinical findings consistent with adhesive capsulitis was used to evaluate the incremental cost-effectiveness of three techniques for administering intraarticular steroid to the glenohumeral joint: landmark based (also called blind), ultrasound guided, and fluoroscopy guided. Input data on cost, probability, and utility estimates were obtained through a comprehensive literature search and from expert opinion. The primary effectiveness outcome was quality-adjusted life years (QALY). Costs were estimated in 2017 U.S. dollars. Ultrasound-guided injections were the dominant strategy for the base case, because it was the least expensive ($1280) and most effective (0.4096 QALY) strategy of the three options overall. The model was sensitive to the probabilities of getting the steroid into the joint by means of blind, ultrasound-guided, and fluoroscopy-guided techniques and to the costs of the ultrasound-guided and blind techniques. Two-way sensitivity analyses showed that ultrasound-guided injections were favored over blind and fluoroscopy-guided injections over a range of reasonable probabilities and costs. Probabilistic sensitivity analysis showed that ultrasound-guided injections were cost-effective in 44% of simulations, compared with 34% for blind injections and 22% for fluoroscopy-guided injections and over a wide range of willingness-to-pay thresholds. Ultrasound-guided injections are the most cost-effective option for the initial steroid-based treatment of patients with adhesive capsulitis. Blind and fluoroscopy-guided injections can also be cost-effective when performed by a clinician likely to accurately administer the medication into the
-
Feature-Based Statistical Analysis of Combustion Simulation Data
Energy Technology Data Exchange (ETDEWEB)
Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T
2011-11-18
We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion
-
Comparison of ultrasound-guided versus anatomical landmark ...
African Journals Online (AJOL)
Background Femoral vein cannulation may be required during major surgery in infants and children and may prove to be life saving under certain conditions. This study compared ultrasound (US)-guided cannulation of the femoral vein in infants with the traditional anatomical landmark-guided technique. Methods Eighty ...
-
Machado, Inês; Toews, Matthew; Luo, Jie; Unadkat, Prashin; Essayed, Walid; George, Elizabeth; Teodoro, Pedro; Carvalho, Herculano; Martins, Jorge; Golland, Polina; Pieper, Steve; Frisken, Sarah; Golby, Alexandra; Wells, William
2018-06-04
The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.
-
[Inferring landmark displacements from changes in cephalometric angles].
Xu, T; Baumrind, S
2001-07-01
To investigate the appropriateness of using changes in angular measurements to reflect the actually profile changes. The sample consists of 48 growing malocclusion patients, contained 24 Class I and 24 Class II subjects, treated by an experienced orthodontist using Edgewise technique. Landmark and superimpositional data were extracted from the previously prepared numerical database. Three pairs of angular and linear measures were computed by the Craniofacial Software Package. Although the associations between all three angular measures and their corresponding linear measures are statistically significant at the 0.001 level, the disagreement between these three pairs of measures are 10.4%, 22.9% and 37.5% respectively in this sample. The direction of displacement of anterior facial landmarks during growth and treatment cannot reliably be inferred merely from changes in cephalometric Angles.
-
Interactive music composition driven by feature evolution.
Kaliakatsos-Papakostas, Maximos A; Floros, Andreas; Vrahatis, Michael N
2016-01-01
Evolutionary music composition is a prominent technique for automatic music generation. The immense adaptation potential of evolutionary algorithms has allowed the realisation of systems that automatically produce music through feature and interactive-based composition approaches. Feature-based composition employs qualitatively descriptive music features as fitness landmarks. Interactive composition systems on the other hand, derive fitness directly from human ratings and/or selection. The paper at hand introduces a methodological framework that combines the merits of both evolutionary composition methodologies. To this end, a system is presented that is organised in two levels: the higher level of interaction and the lower level of composition. The higher level incorporates the particle swarm optimisation algorithm, along with a proposed variant and evolves musical features according to user ratings. The lower level realizes feature-based music composition with a genetic algorithm, according to the top level features. The aim of this work is not to validate the efficiency of the currently utilised setup in each level, but to examine the convergence behaviour of such a two-level technique in an objective manner. Therefore, an additional novelty in this work concerns the utilisation of artificial raters that guide the system through the space of musical features, allowing the exploration of its convergence characteristics: does the system converge to optimal melodies, is this convergence fast enough for potential human listeners and is the trajectory to convergence "interesting' and "creative" enough? The experimental results reveal that the proposed methodological framework represents a fruitful and robust, novel approach to interactive music composition.
-
Three dimensional pattern recognition using feature-based indexing and rule-based search
Lee, Jae-Kyu
In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size
-
Directory of Open Access Journals (Sweden)
Ying Chen
2017-06-01
Full Text Available A remembered saccade target could be encoded in egocentric coordinates such as gaze-centered, or relative to some external allocentric landmark that is independent of the target or gaze (landmark-centered. In comparison to egocentric mechanisms, very little is known about such a landmark-centered representation. Here, we used an event-related fMRI design to identify brain areas supporting these two types of spatial coding (i.e., landmark-centered vs. gaze-centered for target memory during the Delay phase where only target location, not saccade direction, was specified. The paradigm included three tasks with identical display of visual stimuli but different auditory instructions: Landmark Saccade (remember target location relative to a visual landmark, independent of gaze, Control Saccade (remember original target location relative to gaze fixation, independent of the landmark, and a non-spatial control, Color Report (report target color. During the Delay phase, the Control and Landmark Saccade tasks activated overlapping areas in posterior parietal cortex (PPC and frontal cortex as compared to the color control, but with higher activation in PPC for target coding in the Control Saccade task and higher activation in temporal and occipital cortex for target coding in Landmark Saccade task. Gaze-centered directional selectivity was observed in superior occipital gyrus and inferior occipital gyrus, whereas landmark-centered directional selectivity was observed in precuneus and midposterior intraparietal sulcus. During the Response phase after saccade direction was specified, the parietofrontal network in the left hemisphere showed higher activation for rightward than leftward saccades. Our results suggest that cortical activation for coding saccade target direction relative to a visual landmark differs from gaze-centered directional selectivity for target memory, from the mechanisms for other types of allocentric tasks, and from the directionally
-
Goyette, Sharon Ramos; McCoy, John G; Kennedy, Ashley; Sullivan, Meghan
2012-02-28
It has been well-established that men outperform women on some spatial tasks. The tools commonly used to demonstrate this difference (e.g. The Mental Rotations Task) typically involve problems and solutions that are presented in a context devoid of referents. The study presented here assessed whether the addition of referents (or "landmarks") would attenuate the well-established sex difference on the judgment of line orientation task (JLOT). Three versions of the JLOT were presented in a within design. The first iteration contained the original JLOT (JLOT 1). JLOT 2 contained three "landmarks" or referents and JLOT 3 contained only one landmark. The sex difference on JLOT 1 was completely negated by the addition of three landmarks on JLOT 2 or the addition of one landmark on JLOT3. In addition, salivary testosterone was measured. In men, gains in performance on the JLOT due to the addition of landmarks were positively correlated with testosterone levels. This suggests that men with the highest testosterone levels benefited the most from the addition of landmarks. These data help to highlight different strategies used by men and women to solve spatial tasks. Copyright © 2011 Elsevier Inc. All rights reserved.
-
Unconscious analyses of visual scenes based on feature conjunctions.
Tachibana, Ryosuke; Noguchi, Yasuki
2015-06-01
To efficiently process a cluttered scene, the visual system analyzes statistical properties or regularities of visual elements embedded in the scene. It is controversial, however, whether those scene analyses could also work for stimuli unconsciously perceived. Here we show that our brain performs the unconscious scene analyses not only using a single featural cue (e.g., orientation) but also based on conjunctions of multiple visual features (e.g., combinations of color and orientation information). Subjects foveally viewed a stimulus array (duration: 50 ms) where 4 types of bars (red-horizontal, red-vertical, green-horizontal, and green-vertical) were intermixed. Although a conscious perception of those bars was inhibited by a subsequent mask stimulus, the brain correctly analyzed the information about color, orientation, and color-orientation conjunctions of those invisible bars. The information of those features was then used for the unconscious configuration analysis (statistical processing) of the central bars, which induced a perceptual bias and illusory feature binding in visible stimuli at peripheral locations. While statistical analyses and feature binding are normally 2 key functions of the visual system to construct coherent percepts of visual scenes, our results show that a high-level analysis combining those 2 functions is correctly performed by unconscious computations in the brain. (c) 2015 APA, all rights reserved).
-
The urban features of informal settlements in Jakarta, Indonesia
Directory of Open Access Journals (Sweden)
Waleed Alzamil
2017-12-01
Full Text Available This data article contains the urban features of three informal settlements in Jakarta: A. Kampung Bandan; B. Kampung Luar Batang; And C. Kampung Muara Baru. The data describes the urban features of physical structures, infrastructures, and public services. These data include maps showing locations of these settlements, photography of urban status, and examples of urban fabric. The data are obtained from the statistical records and field surveys of three settlements cases. Keywords: Informal settlements, Physical, Features, Urban, Kampung, Jakarta, Indonesia
-
Looking beyond the Boundaries: Time to Put Landmarks Back on the Cognitive Map?
Lew, Adina R.
2011-01-01
Since the proposal of Tolman (1948) that mammals form maplike representations of familiar environments, cognitive map theory has been at the core of debates on the fundamental mechanisms of animal learning and memory. Traditional formulations of cognitive map theory emphasize relations between landmarks and between landmarks and goal locations as…
-
Driver drowsiness classification using fuzzy wavelet-packet-based feature-extraction algorithm.
Khushaba, Rami N; Kodagoda, Sarath; Lal, Sara; Dissanayake, Gamini
2011-01-01
Driver drowsiness and loss of vigilance are a major cause of road accidents. Monitoring physiological signals while driving provides the possibility of detecting and warning of drowsiness and fatigue. The aim of this paper is to maximize the amount of drowsiness-related information extracted from a set of electroencephalogram (EEG), electrooculogram (EOG), and electrocardiogram (ECG) signals during a simulation driving test. Specifically, we develop an efficient fuzzy mutual-information (MI)- based wavelet packet transform (FMIWPT) feature-extraction method for classifying the driver drowsiness state into one of predefined drowsiness levels. The proposed method estimates the required MI using a novel approach based on fuzzy memberships providing an accurate-information content-estimation measure. The quality of the extracted features was assessed on datasets collected from 31 drivers on a simulation test. The experimental results proved the significance of FMIWPT in extracting features that highly correlate with the different drowsiness levels achieving a classification accuracy of 95%-- 97% on an average across all subjects.
-
Feature Usage Explorer: Usage Monitoring and Visualization Tool in HTML5 Based Applications
Directory of Open Access Journals (Sweden)
Sarunas Marciuska
2013-10-01
Full Text Available Feature Usage Explorer is a JavaScript library, which automatically detects features in HTML5 based applications and monitors their usage. The collected information can be visualized in a Feature Usage Diagram, which is automatically generated from an input json file. Currently, the users of Feature Usage Explorer have to design their own tool in order to generate the json file from collected usage information. This option remains viable when using the library in order not to constraint the user’s choice of preferred data storage. Feature Usage Explorer can be reused in any HTML5 based applications where an understanding of how users interact with the system is required (i.e. user experience and usability studies, human computer interaction field, or requirement prioritization area.
-
An improved algorithm for information hiding based on features of Arabic text: A Unicode approach
Directory of Open Access Journals (Sweden)
A.A. Mohamed
2014-07-01
Full Text Available Steganography means how to hide secret information in a cover media, so that other individuals fail to realize their existence. Due to the lack of data redundancy in the text file in comparison with other carrier files, text steganography is a difficult problem to solve. In this paper, we proposed a new promised steganographic algorithm for Arabic text based on features of Arabic text. The focus is on more secure algorithm and high capacity of the carrier. Our extensive experiments using the proposed algorithm resulted in a high capacity of the carrier media. The embedding capacity rate ratio of the proposed algorithm is high. In addition, our algorithm can resist traditional attacking methods since it makes the changes in carrier text as minimum as possible.
-
IMMAN: free software for information theory-based chemometric analysis.
Urias, Ricardo W Pino; Barigye, Stephen J; Marrero-Ponce, Yovani; García-Jacas, César R; Valdes-Martiní, José R; Perez-Gimenez, Facundo
2015-05-01
The features and theoretical background of a new and free computational program for chemometric analysis denominated IMMAN (acronym for Information theory-based CheMoMetrics ANalysis) are presented. This is multi-platform software developed in the Java programming language, designed with a remarkably user-friendly graphical interface for the computation of a collection of information-theoretic functions adapted for rank-based unsupervised and supervised feature selection tasks. A total of 20 feature selection parameters are presented, with the unsupervised and supervised frameworks represented by 10 approaches in each case. Several information-theoretic parameters traditionally used as molecular descriptors (MDs) are adapted for use as unsupervised rank-based feature selection methods. On the other hand, a generalization scheme for the previously defined differential Shannon's entropy is discussed, as well as the introduction of Jeffreys information measure for supervised feature selection. Moreover, well-known information-theoretic feature selection parameters, such as information gain, gain ratio, and symmetrical uncertainty are incorporated to the IMMAN software ( http://mobiosd-hub.com/imman-soft/ ), following an equal-interval discretization approach. IMMAN offers data pre-processing functionalities, such as missing values processing, dataset partitioning, and browsing. Moreover, single parameter or ensemble (multi-criteria) ranking options are provided. Consequently, this software is suitable for tasks like dimensionality reduction, feature ranking, as well as comparative diversity analysis of data matrices. Simple examples of applications performed with this program are presented. A comparative study between IMMAN and WEKA feature selection tools using the Arcene dataset was performed, demonstrating similar behavior. In addition, it is revealed that the use of IMMAN unsupervised feature selection methods improves the performance of both IMMAN and WEKA
-
Cálculo distribuido de landmarks para sistemas de planificación multiagente
Oropesa Física, Ana
2013-01-01
En este Proyecto Final de Carrera se verá la motivación por la que hacer una heurística multiagente utilizando landmarks, la construcción de ésta y unos posteriores resultados y comparativas con la heurística monoagente entre otras. Oropesa Física, A. (2013). Cálculo distribuido de landmarks para sistemas de planificación multiagente. http://hdl.handle.net/10251/32520. Archivo delegado
-
Deli, Roberto; Di Gioia, Eliana; Galantucci, Luigi Maria; Percoco, Gianluca
2010-01-01
To set up a three-dimensional photogrammetric scanning system for precise landmark measurements, without any physical contact, using a low-cost and noninvasive digital photogrammetric solution, for supporting several necessity in clinical orthodontics and/or surgery diagnosis. Thirty coded targets were directly applied onto the subject's face on the soft tissue landmarks, and then, 3 simultaneous photos were acquired using photogrammetry, at room light conditions. For comparison, a dummy head was digitized both with a photogrammetric technique and with the laser scanner Minolta Vivid 910i (Konica Minolta, Tokyo, Japan). The precise measurement of the landmarks is ranged between 0.017 and 0.029 mm. The system automatically measures spatial position of face landmarks, from which distances and angles can be obtained. The facial measurements were compared with those done using laser scanning and manual caliper. The adopted method gives higher precision than the others (0.022-mm mean value on points and 0.038-mm mean value on linear distances on a dummy head), is simple, and can be used easily as a standard routine. The study demonstrated the validity of photogrammetry for accurate digitization of human face landmarks. This research points out the potential of this low-cost photogrammetry approach for medical digitization.
-
A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification
Wang, Suge; Li, Deyu; Wei, Yingjie; Li, Hongxia
With the rapid growth of e-commerce, product reviews on the Web have become an important information source for customers' decision making when they intend to buy some product. As the reviews are often too many for customers to go through, how to automatically classify them into different sentiment orientation categories (i.e. positive/negative) has become a research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for product review text sentiment classification. In order to validate the validity of the proposed method, we compared it with other methods respectively based on information gain and mutual information while support vector machine is adopted as the classifier. In this paper, 6 subexperiments are conducted by combining different feature selection methods with 2 kinds of candidate feature sets. Under 1006 review documents of cars, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance with F value 83.3% while the candidate features are the words which appear in both positive and negative texts.
-
Analytical Features: A Knowledge-Based Approach to Audio Feature Generation
Directory of Open Access Journals (Sweden)
Pachet François
2009-01-01
Full Text Available We present a feature generation system designed to create audio features for supervised classification tasks. The main contribution to feature generation studies is the notion of analytical features (AFs, a construct designed to support the representation of knowledge about audio signal processing. We describe the most important aspects of AFs, in particular their dimensional type system, on which are based pattern-based random generators, heuristics, and rewriting rules. We show how AFs generalize or improve previous approaches used in feature generation. We report on several projects using AFs for difficult audio classification tasks, demonstrating their advantage over standard audio features. More generally, we propose analytical features as a paradigm to bring raw signals into the world of symbolic computation.
-
A feature-based approach to modeling protein-protein interaction hot spots.
Cho, Kyu-il; Kim, Dongsup; Lee, Doheon
2009-05-01
Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.
-
A feature-based approach to modeling protein–protein interaction hot spots
Cho, Kyu-il; Kim, Dongsup; Lee, Doheon
2009-01-01
Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533
-
A new method for automatic tracking of facial landmarks in 3D motion captured images (4D).
Al-Anezi, T; Khambay, B; Peng, M J; O'Leary, E; Ju, X; Ayoub, A
2013-01-01
The aim of this study was to validate the automatic tracking of facial landmarks in 3D image sequences. 32 subjects (16 males and 16 females) aged 18-35 years were recruited. 23 anthropometric landmarks were marked on the face of each subject with non-permanent ink using a 0.5mm pen. The subjects were asked to perform three facial animations (maximal smile, lip purse and cheek puff) from rest position. Each animation was captured by the 3D imaging system. A single operator manually digitised the landmarks on the 3D facial models and their locations were compared with those of the automatically tracked ones. To investigate the accuracy of manual digitisation, the operator re-digitised the same set of 3D images of 10 subjects (5 male and 5 female) at 1 month interval. The discrepancies in x, y and z coordinates between the 3D position of the manual digitised landmarks and that of the automatic tracked facial landmarks were within 0.17mm. The mean distance between the manually digitised and the automatically tracked landmarks using the tracking software was within 0.55 mm. The automatic tracking of facial landmarks demonstrated satisfactory accuracy which would facilitate the analysis of the dynamic motion during facial animations. Copyright © 2012 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.
-
Social Graph Community Differentiated by Node Features with Partly Missing Information
Directory of Open Access Journals (Sweden)
V. O. Chesnokov
2015-01-01
Full Text Available This paper proposes a new algorithm for community differentiation in social graphs, which uses information both on the graph structure and on the vertices. We consider user's ego-network i.e. his friends, with no himself, where each vertex has a set of features such as details on a workplace, institution, etc. The task is to determine missing or unspecified features of the vertices, based on their neighbors' features, and use these features to differentiate the communities in the social graph. Two vertices are believed to belong to the same community if they have a common feature. A hypothesis has been put forward that if most neighbors of a vertex have a common feature, there is a good probability that the vertex has this feature as well. The proposed algorithm is iterative and updates features of vertices, based on its neighbors, according to the hypothesis. Share of neighbors that form a majority is specified by the algorithm parameter. Complexity of single iteration depends linearly on the number of edges in the graph.To assess the quality of clustering three normalized metrics were used, namely: expected density, silhouette index, and Hubert's Gamma Statistic. The paper describes a method for test sampling of 2.000 graphs of the user's social network \\VKontakte". The API requests addressed \\VKontakte" and parsing HTML-pages of user's profiles and search results provided crawling. Information on user's group membership, secondary and higher education, and workplace was used as features. To store data the PostgreSQL DBMS was used, and the gexf format was used for data processing. For the test sample, metrics for several values of algorithm parameter were estimated: the value of index silhouettes was low (0.14-0.20, but within the normal range; the value of expected density was high, i.e. 1.17-1.52; the value of Hubert's gamma statistic was 0.94-0.95 that is close to the maximum. The number of vertices with no features was calculated before
-
An ant colony optimization based feature selection for web page classification.
Saraç, Esra; Özel, Selma Ayşe
2014-01-01
The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.
-
A novel murmur-based heart sound feature extraction technique using envelope-morphological analysis
Yao, Hao-Dong; Ma, Jia-Li; Fu, Bin-Bin; Wang, Hai-Yang; Dong, Ming-Chui
2015-07-01
Auscultation of heart sound (HS) signals serves as an important primary approach to diagnose cardiovascular diseases (CVDs) for centuries. Confronting the intrinsic drawbacks of traditional HS auscultation, computer-aided automatic HS auscultation based on feature extraction technique has witnessed explosive development. Yet, most existing HS feature extraction methods adopt acoustic or time-frequency features which exhibit poor relationship with diagnostic information, thus restricting the performance of further interpretation and analysis. Tackling such a bottleneck problem, this paper innovatively proposes a novel murmur-based HS feature extraction method since murmurs contain massive pathological information and are regarded as the first indications of pathological occurrences of heart valves. Adapting discrete wavelet transform (DWT) and Shannon envelope, the envelope-morphological characteristics of murmurs are obtained and three features are extracted accordingly. Validated by discriminating normal HS and 5 various abnormal HS signals with extracted features, the proposed method provides an attractive candidate in automatic HS auscultation.
-
Langenderfer, Joseph E; Rullkoetter, Paul J; Mell, Amy G; Laz, Peter J
2009-04-01
An accurate assessment of shoulder kinematics is useful for understanding healthy normal and pathological mechanics. Small variability in identifying and locating anatomical landmarks (ALs) has potential to affect reported shoulder kinematics. The objectives of this study were to quantify the effect of landmark location variability on scapular and humeral kinematic descriptions for multiple subjects using probabilistic analysis methods, and to evaluate the consistency in results across multiple subjects. Data from 11 healthy subjects performing humeral elevation in the scapular plane were used to calculate Euler angles describing humeral and scapular kinematics. Probabilistic analyses were performed for each subject to simulate uncertainty in the locations of 13 upper-extremity ALs. For standard deviations of 4 mm in landmark location, the analysis predicted Euler angle envelopes between the 1 and 99 percentile bounds of up to 16.6 degrees . While absolute kinematics varied with the subject, the average 1-99% kinematic ranges for the motion were consistent across subjects and sensitivity factors showed no statistically significant differences between subjects. The description of humeral kinematics was most sensitive to the location of landmarks on the thorax, while landmarks on the scapula had the greatest effect on the description of scapular elevation. The findings of this study can provide a better understanding of kinematic variability, which can aid in making accurate clinical diagnoses and refining kinematic measurement techniques.
-
Feature-based component model for design of embedded systems
Zha, Xuan Fang; Sriram, Ram D.
2004-11-01
An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.
-
Yoon, Kaeng Won; Yoon, Suk-Ja; Kang, Byung-Cheol; Kim, Young-Hee; Kook, Min Suk; Lee, Jae-Seo; Palomo, Juan Martin
2014-09-01
This study aimed to investigate the deviation of landmarks from horizontal or midsagittal reference planes according to the methods of establishing reference planes. Computed tomography (CT) scans of 18 patients who received orthodontic and orthognathic surgical treatment were reviewed. Each CT scan was reconstructed by three methods for establishing three orthogonal reference planes (namely, the horizontal, midsagittal, and coronal reference planes). The horizontal (bilateral porions and bilateral orbitales) and midsagittal (crista galli, nasion, prechiasmatic point, opisthion, and anterior nasal spine) landmarks were identified on each CT scan. Vertical deviation of the horizontal landmarks and horizontal deviation of the midsagittal landmarks were measured. The porion and orbitale, which were not involved in establishing the horizontal reference plane, were found to deviate vertically from the horizontal reference plane in the three methods. The midsagittal landmarks, which were not used for the midsagittal reference plane, deviated horizontally from the midsagittal reference plane in the three methods. In a three-dimensional facial analysis, the vertical and horizontal deviations of the landmarks from the horizontal and midsagittal reference planes could vary depending on the methods of establishing reference planes.
-
International Nuclear Information System (INIS)
Yoon, Kaeng Won; Yoon, Suk Ja; Kang, Byung Cheol; Kook, Min Suk; Lee, Jae Seo; Kim, Young Hee; Palomo, Juan Martin
2014-01-01
This study aimed to investigate the deviation of landmarks from horizontal or midsagittal reference planes according to the methods of establishing reference planes. Computed tomography (CT) scans of 18 patients who received orthodontic and orthognathic surgical treatment were reviewed. Each CT scan was reconstructed by three methods for establishing three orthogonal reference planes (namely, the horizontal, midsagittal, and coronal reference planes). The horizontal (bilateral porions and bilateral orbitales) and midsagittal (crista galli, nasion, prechiasmatic point, opisthion, and anterior nasal spine) landmarks were identified on each CT scan. Vertical deviation of the horizontal landmarks and horizontal deviation of the midsagittal landmarks were measured. The porion and orbitale, which were not involved in establishing the horizontal reference plane, were found to deviate vertically from the horizontal reference plane in the three methods. The midsagittal landmarks, which were not used for the midsagittal reference plane, deviated horizontally from the midsagittal reference plane in the three methods. In a three-dimensional facial analysis, the vertical and horizontal deviations of the landmarks from the horizontal and midsagittal reference planes could vary depending on the methods of establishing reference planes.
-
Energy Technology Data Exchange (ETDEWEB)
Yoon, Kaeng Won; Yoon, Suk Ja; Kang, Byung Cheol; Kook, Min Suk; Lee, Jae Seo [School of Dentistry, Dental Science Research Institute, Chonnam National University, Gwangju (Korea, Republic of); Kim, Young Hee [Dept. of Oral and Maxillofacial Radiology, Hallym University Sacred Heart Hospital, Anyang (Korea, Republic of); Palomo, Juan Martin [Dept. of Orthodontics, School of Dental Medicine, Case Western Reserve University, Cleveland (Korea, Republic of)
2014-09-15
This study aimed to investigate the deviation of landmarks from horizontal or midsagittal reference planes according to the methods of establishing reference planes. Computed tomography (CT) scans of 18 patients who received orthodontic and orthognathic surgical treatment were reviewed. Each CT scan was reconstructed by three methods for establishing three orthogonal reference planes (namely, the horizontal, midsagittal, and coronal reference planes). The horizontal (bilateral porions and bilateral orbitales) and midsagittal (crista galli, nasion, prechiasmatic point, opisthion, and anterior nasal spine) landmarks were identified on each CT scan. Vertical deviation of the horizontal landmarks and horizontal deviation of the midsagittal landmarks were measured. The porion and orbitale, which were not involved in establishing the horizontal reference plane, were found to deviate vertically from the horizontal reference plane in the three methods. The midsagittal landmarks, which were not used for the midsagittal reference plane, deviated horizontally from the midsagittal reference plane in the three methods. In a three-dimensional facial analysis, the vertical and horizontal deviations of the landmarks from the horizontal and midsagittal reference planes could vary depending on the methods of establishing reference planes.
-
MAP Fault Localization Based on Wide Area Synchronous Phasor Measurement Information
Zhang, Yagang; Wang, Zengping
2015-02-01
In the research of complicated electrical engineering, the emergence of phasor measurement units (PMU) is a landmark event. The establishment and application of wide area measurement system (WAMS) in power system has made widespread and profound influence on the safe and stable operation of complicated power system. In this paper, taking full advantage of wide area synchronous phasor measurement information provided by PMUs, we have carried out precise fault localization based on the principles of maximum posteriori probability (MAP). Large numbers of simulation experiments have confirmed that the results of MAP fault localization are accurate and reliable. Even if there are interferences from white Gaussian stochastic noise, the results from MAP classification are also identical to the actual real situation.
-
Features of information policy in the Nordic countries
Directory of Open Access Journals (Sweden)
P. A. Strunin
2014-06-01
A result of research features implementation of information policy in the Nordic countries it is possible to identify common characteristics of all the countries: access to information; create a national information potential; use of information resources in the national interest; create a common health information; promote international cooperation in the field of communication and information; warranty information sovereignty of the state; development of information infrastructure; development of egovernment; enhance information literacy; use of ICT in all spheres of society – the economy, education, medicine and so on.
-
Directory of Open Access Journals (Sweden)
Li Dongmei
2009-05-01
Full Text Available Abstract Background Universally accepted landmark stages are necessary to highlight key events in plant reproductive development and to facilitate comparisons among species. Domestication and selection of tomato resulted in many varieties that differ in fruit shape and size. This diversity is useful to unravel underlying molecular and developmental mechanisms that control organ morphology and patterning. The tomato fruit shape gene SUN controls fruit elongation. The most dramatic effect of SUN on fruit shape occurs after pollination and fertilization although a detailed investigation into the timing of the fruit shape change as well as gene expression profiles during critical developmental stages has not been conducted. Results We provide a description of floral and fruit development in a red-fruited closely related wild relative of tomato, Solanum pimpinellifolium accession LA1589. We use established and propose new floral and fruit landmarks to present a framework for tomato developmental studies. In addition, gene expression profiles of three key stages in floral and fruit development are presented, namely floral buds 10 days before anthesis (floral landmark 7, anthesis-stage flowers (floral landmark 10 and fruit landmark 1, and 5 days post anthesis fruit (fruit landmark 3. To demonstrate the utility of the landmarks, we characterize the tomato shape gene SUN in fruit development. SUN controls fruit shape predominantly after fertilization and its effect reaches a maximum at 8 days post-anthesis coinciding with fruit landmark 4 representing the globular embryo stage of seed development. The expression profiles of the NILs that differ at sun show that only 34 genes were differentially expressed and most of them at a less than 2-fold difference. Conclusion The landmarks for flower and fruit development in tomato were outlined and integrated with the effect of SUN on fruit shape. Although we did not identify many genes differentially expressed in
-
Intensity-based hierarchical elastic registration using approximating splines.
Serifovic-Trbalic, Amira; Demirovic, Damir; Cattin, Philippe C
2014-01-01
We introduce a new hierarchical approach for elastic medical image registration using approximating splines. In order to obtain the dense deformation field, we employ Gaussian elastic body splines (GEBS) that incorporate anisotropic landmark errors and rotation information. Since the GEBS approach is based on a physical model in form of analytical solutions of the Navier equation, it can very well cope with the local as well as global deformations present in the images by varying the standard deviation of the Gaussian forces. The proposed GEBS approximating model is integrated into the elastic hierarchical image registration framework, which decomposes a nonrigid registration problem into numerous local rigid transformations. The approximating GEBS registration scheme incorporates anisotropic landmark errors as well as rotation information. The anisotropic landmark localization uncertainties can be estimated directly from the image data, and in this case, they represent the minimal stochastic localization error, i.e., the Cramér-Rao bound. The rotation information of each landmark obtained from the hierarchical procedure is transposed in an additional angular landmark, doubling the number of landmarks in the GEBS model. The modified hierarchical registration using the approximating GEBS model is applied to register 161 image pairs from a digital mammogram database. The obtained results are very encouraging, and the proposed approach significantly improved all registrations comparing the mean-square error in relation to approximating TPS with the rotation information. On artificially deformed breast images, the newly proposed method performed better than the state-of-the-art registration algorithm introduced by Rueckert et al. (IEEE Trans Med Imaging 18:712-721, 1999). The average error per breast tissue pixel was less than 2.23 pixels compared to 2.46 pixels for Rueckert's method. The proposed hierarchical elastic image registration approach incorporates the GEBS
-
Ometto, Giovanni; Calivá, Francesco; Al-Diri, Bashir; Bek, Toke; Hunter, Andrew
2016-03-01
Automatic, quick and reliable identification of retinal landmarks from fundus photography is key for measurements used in research, diagnosis, screening and treating of common diseases affecting the eyes. This study presents a fast method for the detection of the centre of mass of the vascular arcades, optic nerve head (ONH) and fovea, used in the definition of five clinically relevant areas in use for screening programmes for diabetic retinopathy (DR). Thirty-eight fundus photographs showing 7203 DR lesions were analysed to find the landmarks manually by two retina-experts and automatically by the proposed method. The automatic identification of the ONH and fovea were performed using template matching based on normalised cross correlation. The centre of mass of the arcades was obtained by fitting an ellipse on sample coordinates of the main vessels. The coordinates were obtained by processing the image with hessian filtering followed by shape analyses and finally sampling the results. The regions obtained manually and automatically were used to count the retinal lesions falling within, and to evaluate the method. 92.7% of the lesions were falling within the same regions based on the landmarks selected by the two experts. 91.7% and 89.0% were counted in the same areas identified by the method and the first and second expert respectively. The inter-repeatability of the proposed method and the experts is comparable, while the 100% intra-repeatability makes the algorithm a valuable tool in tasks like analyses in real-time, of large datasets and of intra-patient variability.
-
Directory of Open Access Journals (Sweden)
Moshkelgosha V
2014-12-01
Full Text Available Statement of Problem: Recognition and determination of facial and dental midline is important in dentistry. Currently, there are no verifiable guidelines that direct the choice of specific anatomic landmarks to determine the midline of the face or mouth. Objectives: The purpose of this study was to determine which of facial anatomic landmarks is closest to the midline of the face as well as that of the mouth. Materials and Methods: Frontal full-face digital images of 92 subjects (men and women age range: 20-30 years in smile were taken under standardized conditions; commonly used anatomic landmarks, nasion, tip of the nose, and tip of the philtrum were digitized on the images of subjects and aesthetic analyzer software used for midline analysis using Esthetic Frame. Deviations from the midlines of the face and mouth were measured for the 3 clinical landmarks; the existing dental midline was considered as the fourth landmark. The entire process of midline analysis was done by a single observer and repeated twice. Reliability analysis and 1-sample t- tests were conducted. Results: The Intra-class correlation coefficients (ICCs for reliability analysis of RFV and RCV measures made two times revealed that the reliabilities were all acceptable. The results indicated that each of the 4 landmarks deviated uniquely and significantly (P<.001 from the midlines of the face as well as mouth in both males and females. Conclusions: There was a significant difference between the mean ratios of the chosen anatomic landmarks and the midlines of the face and mouth. The hierarchy of anatomic landmarks closest to the midline of the face is: (1 midline of the commissures, (2 nasion , (3 tip of philtrum,(4 dental midline, and (5 tip ofthe nose. The closest anatomic landmarks to the mouth midline are: (1 tip of philtrum, (2 dental midline, (3 tip of nose, and (4 nasion.
-
Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection
Directory of Open Access Journals (Sweden)
Jaesung Lee
2016-11-01
Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.
-
The algorithm of fast image stitching based on multi-feature extraction
Yang, Chunde; Wu, Ge; Shi, Jing
2018-05-01
This paper proposed an improved image registration method combining Hu-based invariant moment contour information and feature points detection, aiming to solve the problems in traditional image stitching algorithm, such as time-consuming feature points extraction process, redundant invalid information overload and inefficiency. First, use the neighborhood of pixels to extract the contour information, employing the Hu invariant moment as similarity measure to extract SIFT feature points in those similar regions. Then replace the Euclidean distance with Hellinger kernel function to improve the initial matching efficiency and get less mismatching points, further, estimate affine transformation matrix between the images. Finally, local color mapping method is adopted to solve uneven exposure, using the improved multiresolution fusion algorithm to fuse the mosaic images and realize seamless stitching. Experimental results confirm high accuracy and efficiency of method proposed in this paper.
-
A Novel Technique for Shape Feature Extraction Using Content Based Image Retrieval
Directory of Open Access Journals (Sweden)
Dhanoa Jaspreet Singh
2016-01-01
Full Text Available With the advent of technology and multimedia information, digital images are increasing very quickly. Various techniques are being developed to retrieve/search digital information or data contained in the image. Traditional Text Based Image Retrieval System is not plentiful. Since it is time consuming as it require manual image annotation. Also, the image annotation differs with different peoples. An alternate to this is Content Based Image Retrieval (CBIR system. It retrieves/search for image using its contents rather the text, keywords etc. A lot of exploration has been compassed in the range of Content Based Image Retrieval (CBIR with various feature extraction techniques. Shape is a significant image feature as it reflects the human perception. Moreover, Shape is quite simple to use by the user to define object in an image as compared to other features such as Color, texture etc. Over and above, if applied alone, no descriptor will give fruitful results. Further, by combining it with an improved classifier, one can use the positive features of both the descriptor and classifier. So, a tryout will be made to establish an algorithm for accurate feature (Shape extraction in Content Based Image Retrieval (CBIR. The main objectives of this project are: (a To propose an algorithm for shape feature extraction using CBIR, (b To evaluate the performance of proposed algorithm and (c To compare the proposed algorithm with state of art techniques.
-
Directory of Open Access Journals (Sweden)
Georges Hattab
2017-05-01
Full Text Available In order to understand gene function in bacterial life cycles, time lapse bioimaging is applied in combination with different marker protocols in so called microfluidics chambers (i.e., a multi-well plate. In one experiment, a series of T images is recorded for one visual field, with a pixel resolution of 60 nm/px. Any (semi-automatic analysis of the data is hampered by a strong image noise, low contrast and, last but not least, considerable irregular shifts during the acquisition. Image registration corrects such shifts enabling next steps of the analysis (e.g., feature extraction or tracking. Image alignment faces two obstacles in this microscopic context: (a highly dynamic structural changes in the sample (i.e., colony growth and (b an individual data set-specific sample environment which makes the application of landmarks-based alignments almost impossible. We present a computational image registration solution, we refer to as ViCAR: (Visual (Cues based (Adaptive (Registration, for such microfluidics experiments, consisting of (1 the detection of particular polygons (outlined and segmented ones, referred to as visual cues, (2 the adaptive retrieval of three coordinates throughout different sets of frames, and finally (3 an image registration based on the relation of these points correcting both rotation and translation. We tested ViCAR with different data sets and have found that it provides an effective spatial alignment thereby paving the way to extract temporal features pertinent to each resulting bacterial colony. By using ViCAR, we achieved an image registration with 99.9% of image closeness, based on the average rmsd of 4.10−2 pixels, and superior results compared to a state of the art algorithm.
-
TIGER/Line Shapefile, 2016, Series Information for the Area Landmark State-based Shapefile
US Census Bureau, Department of Commerce — The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master...
-
Artificially intelligent recognition of Arabic speaker using voice print-based local features
Mahmood, Awais; Alsulaiman, Mansour; Muhammad, Ghulam; Akram, Sheeraz
2016-11-01
Local features for any pattern recognition system are based on the information extracted locally. In this paper, a local feature extraction technique was developed. This feature was extracted in the time-frequency plain by taking the moving average on the diagonal directions of the time-frequency plane. This feature captured the time-frequency events producing a unique pattern for each speaker that can be viewed as a voice print of the speaker. Hence, we referred to this technique as voice print-based local feature. The proposed feature was compared to other features including mel-frequency cepstral coefficient (MFCC) for speaker recognition using two different databases. One of the databases used in the comparison is a subset of an LDC database that consisted of two short sentences uttered by 182 speakers. The proposed feature attained 98.35% recognition rate compared to 96.7% for MFCC using the LDC subset.
-
Training Classifiers with Shadow Features for Sensor-Based Human Activity Recognition.
Fong, Simon; Song, Wei; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L
2017-02-27
In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR) is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion sensor, such as Microsoft Kinect. These skeletal data are the spatial coordinates (x, y, z) of different parts of the human body. The numeric information forms time series, temporal records of movement sequences that can be used for training a classifier. In addition to the spatial features that describe current positions in the skeletal data, new features called 'shadow features' are used to improve the supervised learning efficacy of the classifier. Shadow features are inferred from the dynamics of body movements, and thereby modelling the underlying momentum of the performed activities. They provide extra dimensions of information for characterising activities in the classification process, and thereby significantly improve the classification accuracy. Two cases of HAR are tested using a classification model trained with shadow features: one is by using wearable sensor and the other is by a Kinect-based remote sensor. Our experiments can demonstrate the advantages of the new method, which will have an impact on human activity detection research.
-
Information retrieval system based on INIS tapes
International Nuclear Information System (INIS)
Pultorak, G.
1976-01-01
An information retrieval system based on the INIS computer tapes is described. It includes the three main elements of a computerized information system: a data base on a machine -readable medium, a collection of queries which represent the information needs from the data - base, and a set of programs by which the actual retrieval is done, according to the user's queries. The system is built for the center's computer, a CDC 3600, and its special features characterize, to a certain degree, the structure of the programs. (author)
-
Short text sentiment classification based on feature extension and ensemble classifier
Liu, Yang; Zhu, Xie
2018-05-01
With the rapid development of Internet social media, excavating the emotional tendencies of the short text information from the Internet, the acquisition of useful information has attracted the attention of researchers. At present, the commonly used can be attributed to the rule-based classification and statistical machine learning classification methods. Although micro-blog sentiment analysis has made good progress, there still exist some shortcomings such as not highly accurate enough and strong dependence from sentiment classification effect. Aiming at the characteristics of Chinese short texts, such as less information, sparse features, and diverse expressions, this paper considers expanding the original text by mining related semantic information from the reviews, forwarding and other related information. First, this paper uses Word2vec to compute word similarity to extend the feature words. And then uses an ensemble classifier composed of SVM, KNN and HMM to analyze the emotion of the short text of micro-blog. The experimental results show that the proposed method can make good use of the comment forwarding information to extend the original features. Compared with the traditional method, the accuracy, recall and F1 value obtained by this method have been improved.
-
Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R
2015-10-01
This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.
-
Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.
Gutta, Sandeep; Cheng, Qi
2016-03-01
Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.
-
Print advertisements for Alzheimer's disease drugs: informational and transformational features.
Gooblar, Jonathan; Carpenter, Brian D
2013-06-01
We examined print advertisements for Alzheimer's disease drugs published in journals and magazines between January 2008 and February 2012, using an informational versus transformational theoretical framework to identify objective and persuasive features. In 29 unique advertisements, we used qualitative methods to code and interpret identifying information, charts, benefit and side effect language, and persuasive appeals embedded in graphics and narratives. Most elements contained a mixture of informational and transformational features. Charts were used infrequently, but when they did appear the accompanying text often exaggerated the data. Benefit statements covered an array of symptoms, drug properties, and caregiver issues. Side effect statements often used positive persuasive appeals. Graphics and narrative features emphasized positive emotions and outcomes. We found subtle and sophisticated attempts both to educate and to persuade readers. It is important for consumers and prescribing physicians to read print advertisements critically so that they can make informed treatment choices.
-
Elections and landmark policies in Tanzania and Uganda
DEFF Research Database (Denmark)
Kjær, Anne Mette; Therkildsen, Ole
2013-01-01
Much of the relevant literature on Africa downplays the salience of elections for policy-making and implementation. Instead, the importance of factors such as clientelism, ethnicity, organized interest group and donor influence, is emphasized. We argue that, in addition, elections now motivate...... political elites to focus on policies they perceive to be able to gain votes. This is based on analyses of six landmark decisions made during the last fifteen years in the social, productive and public finance sectors in Tanzania and Uganda. Such policies share a number of key characteristics......: they are clearly identifiable with the party in power; citizens country-wide are targeted; and policy implementation aim at immediate, visible results. The influence of elections on policy making and implementation could therefore be more significant in countries where elections are more competitive than...
-
Detection of relationships among multi-modal brain imaging meta-features via information flow.
Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D
2018-01-15
Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is
-
FAST DISCRETE CURVELET TRANSFORM BASED ANISOTROPIC FEATURE EXTRACTION FOR IRIS RECOGNITION
Directory of Open Access Journals (Sweden)
Amol D. Rahulkar
2010-11-01
Full Text Available The feature extraction plays a very important role in iris recognition. Recent researches on multiscale analysis provide good opportunity to extract more accurate information for iris recognition. In this work, a new directional iris texture features based on 2-D Fast Discrete Curvelet Transform (FDCT is proposed. The proposed approach divides the normalized iris image into six sub-images and the curvelet transform is applied independently on each sub-image. The anisotropic feature vector for each sub-image is derived using the directional energies of the curvelet coefficients. These six feature vectors are combined to create the resultant feature vector. During recognition, the nearest neighbor classifier based on Euclidean distance has been used for authentication. The effectiveness of the proposed approach has been tested on two different databases namely UBIRIS and MMU1. Experimental results show the superiority of the proposed approach.
-
Clements, Logan W.; Chapman, William C.; Dawant, Benoit M.; Galloway, Robert L.; Miga, Michael I.
2008-01-01
A successful surface-based image-to-physical space registration in image-guided liver surgery (IGLS) is critical to provide reliable guidance information to surgeons and pertinent surface displacement data for use in deformation correction algorithms. The current protocol used to perform the image-to-physical space registration involves an initial pose estimation provided by a point based registration of anatomical landmarks identifiable in both the preoperative tomograms and the intraoperati...
-
An Improved Iris Recognition Algorithm Based on Hybrid Feature and ELM
Wang, Juan
2018-03-01
The iris image is easily polluted by noise and uneven light. This paper proposed an improved extreme learning machine (ELM) based iris recognition algorithm with hybrid feature. 2D-Gabor filters and GLCM is employed to generate a multi-granularity hybrid feature vector. 2D-Gabor filter and GLCM feature work for capturing low-intermediate frequency and high frequency texture information, respectively. Finally, we utilize extreme learning machine for iris recognition. Experimental results reveal our proposed ELM based multi-granularity iris recognition algorithm (ELM-MGIR) has higher accuracy of 99.86%, and lower EER of 0.12% under the premise of real-time performance. The proposed ELM-MGIR algorithm outperforms other mainstream iris recognition algorithms.
-
Informational economy: specific features and challenges of monopolization
Kotsofana, T.
2013-01-01
The article discusses the features of the informational economy, as well as some issues with which this economy is facing today. In particular, contemporary forms of monopoly, its causes and consequences, changing trends towards monopolization and monopolization of markets due to the high degree of automation and information of the socio-economic life were analyzed.
-
Directory of Open Access Journals (Sweden)
Keranmu Xielifuguli
2014-01-01
Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.
-
Tolerance-Based Feature Transforms
Reniers, Dennie; Telea, Alexandru
2007-01-01
Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs on binary
-
A stereo remote sensing feature selection method based on artificial bee colony algorithm
Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi
2014-05-01
To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.
-
Collaborative Tracking of Image Features Based on Projective Invariance
Jiang, Jinwei
In past manned lunar landing missions, such as Apollo 14, spatial disorientation of astronauts substantially compromised the productivities of astronauts, and caused safety and mission success problems. The non-GPS lunar environment has micro-gravity field, and lacks both spatial recognition cues and reference objects which are familiar to the human biological sensors related to spatial recognition (e.g. eyes). Such an environment causes misperceptions of the locations of astronauts and targets and their spatial relations, as well as misperceptions of the heading direction and travel distances of astronauts. These spatial disorientation effects can reduce productivity and cause life risks in lunar manned missions. A navigation system, which is capable of locating astronauts and tracking the movements of them on the lunar surface, is critical for future lunar manned missions where multiple astronauts will traverse more than 100km from the lander or the base station with the assistance from roving vehicle, and need real-time navigation support for effective collaborations among them. Our earlier research to solve these problems dealt with developing techniques to enable a precise, flexible and reliable Lunar Astronaut Spatial Orientation and Information System (LASOIS) capable of delivering real-time navigation information to astronauts on the lunar surface. The LASOIS hardware was a sensor network composed of orbital, ground and on-suit sensors: the Lunar Reconnaissance Orbiter Camera (LROC), radio beacons, the on-suit cameras, and shoe-mounted Inertial Measurement Unit (IMU). The LASOIS software included efficient and robust algorithms for estimating trajectory from IMU signals, generating heading information from imagery acquired from on-suit cameras, and an Extended Kalman Filter (EKF) based approach for integrating these spatial information components to generate the trajectory of an astronaut with meter-level accuracy. Moreover, LASOIS emphasized multi
-
Almukhtar, Anas; Khambay, Balvinder; Ayoub, Ashraf; Ju, Xiangyang; Al-Hiyali, Ali; Macdonald, James; Jabar, Norhayati; Goto, Tazuko
2015-01-01
The limitations of the current methods of quantifying the surgical movements of facial bones inspired this study. The aim of this study was the assessment of the accuracy and reproducibility of directly landmarking of 3D DICOM images (Digital Imaging and Communications in Medicine) to quantify the changes in the jaw bones following surgery. The study was carried out on plastic skull to simulate the surgical movements of the jaw bones. Cone beam CT scans were taken at 3mm, 6mm, and 9mm maxillary advancement; together with a 2mm, 4mm, 6mm and 8mm "down graft" which in total generated 12 different positions of the maxilla for the analysis. The movements of the maxilla were calculated using two methods, the standard approach where distances between surface landmarks on the jaw bones were measured and the novel approach where measurements were taken directly from the internal structures of the corresponding 3D DICOME slices. A one sample t-test showed that there was no statistically significant difference between the two methods of measurements for the y and z directions, however, the x direction showed a significant difference. The mean difference between the two absolute measurements were 0.34±0.20mm, 0.22±0.16mm, 0.18±0.13mm in the y, z and x directions respectively. In conclusion, the direct landmarking of 3D DICOM image slices is a reliable, reproducible and informative method for assessment of the 3D skeletal changes. The method has a clear clinical application which includes the analysis of the jaw movements "orthognathic surgery" for the correction of facial deformities.
-
Directory of Open Access Journals (Sweden)
Anas Almukhtar
Full Text Available The limitations of the current methods of quantifying the surgical movements of facial bones inspired this study. The aim of this study was the assessment of the accuracy and reproducibility of directly landmarking of 3D DICOM images (Digital Imaging and Communications in Medicine to quantify the changes in the jaw bones following surgery. The study was carried out on plastic skull to simulate the surgical movements of the jaw bones. Cone beam CT scans were taken at 3mm, 6mm, and 9mm maxillary advancement; together with a 2mm, 4mm, 6mm and 8mm "down graft" which in total generated 12 different positions of the maxilla for the analysis. The movements of the maxilla were calculated using two methods, the standard approach where distances between surface landmarks on the jaw bones were measured and the novel approach where measurements were taken directly from the internal structures of the corresponding 3D DICOME slices. A one sample t-test showed that there was no statistically significant difference between the two methods of measurements for the y and z directions, however, the x direction showed a significant difference. The mean difference between the two absolute measurements were 0.34±0.20mm, 0.22±0.16mm, 0.18±0.13mm in the y, z and x directions respectively. In conclusion, the direct landmarking of 3D DICOM image slices is a reliable, reproducible and informative method for assessment of the 3D skeletal changes. The method has a clear clinical application which includes the analysis of the jaw movements "orthognathic surgery" for the correction of facial deformities.
-
Annotation-based feature extraction from sets of SBML models.
Alm, Rebekka; Waltemath, Dagmar; Wolfien, Markus; Wolkenhauer, Olaf; Henkel, Ron
2015-01-01
Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models. In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate. Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.
-
Landmark survey tracks decade of changes in India's rural schools ...
International Development Research Centre (IDRC) Digital Library (Canada)
2011-12-21
Dec 21, 2011 ... These are just a few comments from parents of school-aged children in rural ... Landmark survey tracks decade of changes in India's rural schools ... funded by Canada's International Development Research Centre (IDRC).
-
A Mean-Shift-Based Feature Descriptor for Wide Baseline Stereo Matching
Directory of Open Access Journals (Sweden)
Yiwen Dou
2015-01-01
Full Text Available We propose a novel Mean-Shift-based building approach in wide baseline. Initially, scale-invariance feature transform (SIFT approach is used to extract relatively stable feature points. As to each matching SIFT feature point, it needs a reasonable neighborhood range so as to choose feature points set. Subsequently, in view of selecting repeatable and high robust feature points, Mean-Shift controls corresponding feature scale. At last, our approach is employed to depth image acquirement in wide baseline and Graph Cut algorithm optimizes disparity information. Compared with the existing methods such as SIFT, speeded up robust feature (SURF, and normalized cross-correlation (NCC, the presented approach has the advantages of higher robustness and accuracy rate. Experimental results on low resolution image and weak feature description in wide baseline confirm the validity of our approach.
-
Wang, Shijun; Yao, Jianhua; Petrick, Nicholas A.; Summers, Ronald M.
2009-02-01
Colon cancer is the second leading cause of cancer-related deaths in the United States. Computed tomographic colonography (CTC) combined with a computer aided detection system provides a feasible combination for improving colonic polyps detection and increasing the use of CTC for colon cancer screening. To distinguish true polyps from false positives, various features extracted from polyp candidates have been proposed. Most of these features try to capture the shape information of polyp candidates or neighborhood knowledge about the surrounding structures (fold, colon wall, etc.). In this paper, we propose a new set of shape descriptors for polyp candidates based on statistical curvature information. These features, called histogram of curvature features, are rotation, translation and scale invariant and can be treated as complementing our existing feature set. Then in order to make full use of the traditional features (defined as group A) and the new features (group B) which are highly heterogeneous, we employed a multiple kernel learning method based on semi-definite programming to identify an optimized classification kernel based on the combined set of features. We did leave-one-patient-out test on a CTC dataset which contained scans from 50 patients (with 90 6-9mm polyp detections). Experimental results show that a support vector machine (SVM) based on the combined feature set and the semi-definite optimization kernel achieved higher FROC performance compared to SVMs using the two groups of features separately. At a false positive per patient rate of 7, the sensitivity on 6-9mm polyps using the combined features improved from 0.78 (Group A) and 0.73 (Group B) to 0.82 (p<=0.01).
-
Extraction Of Audio Features For Emotion Recognition System Based On Music
Directory of Open Access Journals (Sweden)
Kee Moe Han
2015-08-01
Full Text Available Music is the combination of melody linguistic information and the vocalists emotion. Since music is a work of art analyzing emotion in music by computer is a difficult task. Many approaches have been developed to detect the emotions included in music but the results are not satisfactory because emotion is very complex. In this paper the evaluations of audio features from the music files are presented. The extracted features are used to classify the different emotion classes of the vocalists. Musical features extraction is done by using Music Information Retrieval MIR tool box in this paper. The database of 100 music clips are used to classify the emotions perceived in music clips. Music may contain many emotions according to the vocalists mood such as happy sad nervous bored peace etc. In this paper the audio features related to the emotions of the vocalists are extracted to use in emotion recognition system based on music.
-
Compounding local invariant features and global deformable geometry for medical image registration.
Directory of Open Access Journals (Sweden)
Jianhua Zhang
Full Text Available Using deformable models to register medical images can result in problems of initialization of deformable models and robustness and accuracy of matching of inter-subject anatomical variability. To tackle these problems, a novel model is proposed in this paper by compounding local invariant features and global deformable geometry. This model has four steps. First, a set of highly-repeatable and highly-robust local invariant features, called Key Features Model (KFM, are extracted by an effective matching strategy. Second, local features can be matched more accurately through the KFM for the purpose of initializing a global deformable model. Third, the positional relationship between the KFM and the global deformable model can be used to precisely pinpoint all landmarks after initialization. And fourth, the final pose of the global deformable model is determined by an iterative process with a lower time cost. Through the practical experiments, the paper finds three important conclusions. First, it proves that the KFM can detect the matching feature points well. Second, the precision of landmark locations adjusted by the modeled relationship between KFM and global deformable model is greatly improved. Third, regarding the fitting accuracy and efficiency, by observation from the practical experiments, it is found that the proposed method can improve 6~8% of the fitting accuracy and reduce around 50% of the computational time compared with state-of-the-art methods.
-
An improved feature extraction algorithm based on KAZE for multi-spectral image
Yang, Jianping; Li, Jun
2018-02-01
Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.
-
Finger-vein and fingerprint recognition based on a feature-level fusion method
Yang, Jinfeng; Hong, Bofeng
2013-07-01
Multimodal biometrics based on the finger identification is a hot topic in recent years. In this paper, a novel fingerprint-vein based biometric method is proposed to improve the reliability and accuracy of the finger recognition system. First, the second order steerable filters are used here to enhance and extract the minutiae features of the fingerprint (FP) and finger-vein (FV). Second, the texture features of fingerprint and finger-vein are extracted by a bank of Gabor filter. Third, a new triangle-region fusion method is proposed to integrate all the fingerprint and finger-vein features in feature-level. Thus, the fusion features contain both the finger texture-information and the minutiae triangular geometry structure. Finally, experimental results performed on the self-constructed finger-vein and fingerprint databases are shown that the proposed method is reliable and precise in personal identification.
-
Training Classifiers with Shadow Features for Sensor-Based Human Activity Recognition
Directory of Open Access Journals (Sweden)
Simon Fong
2017-02-01
Full Text Available In this paper, a novel training/testing process for building/using a classification model based on human activity recognition (HAR is proposed. Traditionally, HAR has been accomplished by a classifier that learns the activities of a person by training with skeletal data obtained from a motion sensor, such as Microsoft Kinect. These skeletal data are the spatial coordinates (x, y, z of different parts of the human body. The numeric information forms time series, temporal records of movement sequences that can be used for training a classifier. In addition to the spatial features that describe current positions in the skeletal data, new features called ‘shadow features’ are used to improve the supervised learning efficacy of the classifier. Shadow features are inferred from the dynamics of body movements, and thereby modelling the underlying momentum of the performed activities. They provide extra dimensions of information for characterising activities in the classification process, and thereby significantly improve the classification accuracy. Two cases of HAR are tested using a classification model trained with shadow features: one is by using wearable sensor and the other is by a Kinect-based remote sensor. Our experiments can demonstrate the advantages of the new method, which will have an impact on human activity detection research.
-
Dube, Blaire; Emrich, Stephen M; Al-Aidroos, Naseem
2017-10-01
Across 2 experiments we revisited the filter account of how feature-based attention regulates visual working memory (VWM). Originally drawing from discrete-capacity ("slot") models, the filter account proposes that attention operates like the "bouncer in the brain," preventing distracting information from being encoded so that VWM resources are reserved for relevant information. Given recent challenges to the assumptions of discrete-capacity models, we investigated whether feature-based attention plays a broader role in regulating memory. Both experiments used partial report tasks in which participants memorized the colors of circle and square stimuli, and we provided a feature-based goal by manipulating the likelihood that 1 shape would be probed over the other across a range of probabilities. By decomposing participants' responses using mixture and variable-precision models, we estimated the contributions of guesses, nontarget responses, and imprecise memory representations to their errors. Consistent with the filter account, participants were less likely to guess when the probed memory item matched the feature-based goal. Interestingly, this effect varied with goal strength, even across high probabilities where goal-matching information should always be prioritized, demonstrating strategic control over filter strength. Beyond this effect of attention on which stimuli were encoded, we also observed effects on how they were encoded: Estimates of both memory precision and nontarget errors varied continuously with feature-based attention. The results offer support for an extension to the filter account, where feature-based attention dynamically regulates the distribution of resources within working memory so that the most relevant items are encoded with the greatest precision. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
-
Segmentation of human skull in MRI using statistical shape information from CT data.
Wang, Defeng; Shi, Lin; Chu, Winnie C W; Cheng, Jack C Y; Heng, Pheng Ann
2009-09-01
To automatically segment the skull from the MRI data using a model-based three-dimensional segmentation scheme. This study exploited the statistical anatomy extracted from the CT data of a group of subjects by means of constructing an active shape model of the skull surfaces. To construct a reliable shape model, a novel approach was proposed to optimize the automatic landmarking on the coupled surfaces (i.e., the skull vault) by minimizing the description length that incorporated local thickness information. This model was then used to locate the skull shape in MRI of a different group of patients. Compared with performing landmarking separately on the coupled surfaces, the proposed landmarking method constructed models that had better generalization ability and specificity. The segmentation accuracies were measured by the Dice coefficient and the set difference, and compared with the method based on mathematical morphology operations. The proposed approach using the active shape model based on the statistical skull anatomy presented in the head CT data contributes to more reliable segmentation of the skull from MRI data.
-
Pittayapat, Pisha; Jacobs, Reinhilde; Bornstein, Michael M; Odri, Guillaume A; Lambrichts, Ivo; Willems, Guy; Politis, Constantinus; Olszewski, Raphael
2018-05-25
To assess the reproducibility of landmarks in three dimensions that determine the Frankfort horizontal plane (FH) as well as two new landmarks, and to evaluate the angular differences of newly introduced planes to the FH. Three-dimensional (3D) surface models were created from CBCT scans of 26 dry human skulls. Porion (Po), orbitale (Or), internal acoustic foramen (IAF), and zygomatico-maxillary suture (ZyMS) were indicated in the software by three observers twice with a 4-week interval. Angles between two FHs (FH 1: Or-R, Or-L, mid-Po; FH 2: Po-R, Po-L, mid-Or) and between FHs and new planes (Plane 1-6) were measured. Coordinates were exported to a spreadsheet. A statistical analysis was performed to define the landmark reproducibility and 3D angles. Intra- and inter-observer landmark reproducibility showed mean difference more than 1 mm for x-coordinates of all landmarks except IAF. IAF showed significantly better reproducibility than other landmarks (P Plane 3, connecting Or-R, Or-L and mid-IAF, and Plane 4, connecting Po-R, Po-L and mid-ZyMS, both showed an angular difference of less than 1 degree when compared to FHs. This study revealed poor reproducibility of the traditional FH landmarks on the x-axis and good reproducibility of a new landmark tested to replace Po, the IAF. Yet, Or showed superior results compared to ZyMS. The potential of using new horizontal planes was demonstrated. Future studies should focus on identification of a valid alternative for Or and ZyMS and on clinical implementation of the findings.
-
Gas Classification Using Combined Features Based on a Discriminant Analysis for an Electronic Nose
Directory of Open Access Journals (Sweden)
Sang-Il Choi
2016-01-01
Full Text Available This paper proposes a gas classification method for an electronic nose (e-nose system, for which combined features that have been configured through discriminant analysis are used. First, each global feature is extracted from the entire measurement section of the data samples, while the same process is applied to the local features of the section that corresponds to the stabilization, exposure, and purge stages. The discriminative information amounts in the individual features are then measured based on the discriminant analysis, and the combined features are subsequently composed by selecting the features that have a large amount of discriminative information. Regarding a variety of volatile organic compound data, the results of the experiment show that, in a noisy environment, the proposed method exhibits classification performance that is relatively excellent compared to the other feature types.
-
Review of research in feature based design
Salomons, O.W.; van Houten, Frederikus J.A.M.; Kals, H.J.J.
1993-01-01
Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems
-
Ye, Yingjiang; Shen, Zhanlong; Wang, Shan
2014-11-01
Abominoperineal resection (APR) is the main approach of lower rectal cancer treatment. Recently, it was found that conventional APR had higher incidence rate of positive circumferential resection margin(CRM) and intraoperative perforation (IOP), which was the crucial reason of local recurrence and worse prognosis. Extralevator abdominoperineal excision(ELAPE) procedure was proposed by European panels including surgeons, radiologist and pathologists, and considered to lower the positive rates of CRM and IOP. Definitive surgical planes and anatomic landmarks are the cores of this procedure, which are the prerequisite for the guarantee of safety and smoothness of surgery. To realize the anatomy of muscles, fascias, blood vessels and nervous of perineal region is the base of carrying out ELAPE procedure. In this paper, we introduce the key anatomy related to ELAPE procedure and summarize the principle of ELAPE procedure as "two planes and four landmarks", which will be beneficial to the popularization and application.
-
Two-Stream Transformer Networks for Video-based Face Alignment.
Liu, Hao; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie
2017-08-01
In this paper, we propose a two-stream transformer networks (TSTN) approach for video-based face alignment. Unlike conventional image-based face alignment approaches which cannot explicitly model the temporal dependency in videos and motivated by the fact that consistent movements of facial landmarks usually occur across consecutive frames, our TSTN aims to capture the complementary information of both the spatial appearance on still frames and the temporal consistency information across frames. To achieve this, we develop a two-stream architecture, which decomposes the video-based face alignment into spatial and temporal streams accordingly. Specifically, the spatial stream aims to transform the facial image to the landmark positions by preserving the holistic facial shape structure. Accordingly, the temporal stream encodes the video input as active appearance codes, where the temporal consistency information across frames is captured to help shape refinements. Experimental results on the benchmarking video-based face alignment datasets show very competitive performance of our method in comparisons to the state-of-the-arts.
-
Directory of Open Access Journals (Sweden)
Taigang Liu
2015-12-01
Full Text Available The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to address this problem, it is still a challenging topic in the field of bioinformatics. The position-specific score matrix (PSSM profile has been shown to provide a useful source of information for improving the prediction performance of protein structural class. However, this information has not been adequately explored. To this end, in this study, we present a feature extraction technique which is based on gapped-dipeptides composition computed directly from PSSM. Then, a careful feature selection technique is performed based on support vector machine-recursive feature elimination (SVM-RFE. These optimal features are selected to construct a final predictor. The results of jackknife tests on four working datasets show that our method obtains satisfactory prediction accuracies by extracting features solely based on PSSM and could serve as a very promising tool to predict protein structural class.
-
Topographic anatomy of the great auricular point: landmarks for its localization and classification.
Raikos, Athanasios; English, Thomas; Yousif, Omar Khalid; Sandhu, Mandeep; Stirling, Allan
2017-05-01
The great auricular point (GAP) marks the exit of the great auricular nerve at the posterior border of the sternocleidomastoid muscle (SCM). It is a key landmark for the identification of the spinal accessory nerve, and its intraoperative localization is vital to avoid neurological sequelae. This study delineates the topography and surface anatomy landmarks that used to localize the GAP. Thirty cadaveric heminecks were dissected on a layer-by-layer approach. The topography of the GAP was examined relative to the insertion point of the SCM at the clavicle, tip of the mastoid process, and angle of the mandible. The GAP and its relation to the SCM were determined as a ratio of the total length of the SCM. The GAP was demonstrated to be in a predictable location. The mean length of the SCM was 131.4 ± 22 mm, and the mean distance between the GAP and the mastoid process was found to be 60.4 ± 13.76 mm. The ratio of the GAP location to the total SCM length ranged between 0.33-0.57. The mean distance between the angle of the mandible and the GAP was determined to be 57 ± 22.2 mm. Based on the midpoint of the SCM, the GAP was above it in 66.7 % of subjects and classified to Type A, and below it in 33.3 % of subjects appointed to Type B. The anatomical landmarks utilized in this study are helpful in predicting the location of the GAP relative to the midpoint of the SCM and can reduce neural injuries within the posterior triangle of the neck.
-
Feature-Based versus Category-Based Induction with Uncertain Categories
Griffiths, Oren; Hayes, Brett K.; Newell, Ben R.
2012-01-01
Previous research has suggested that when feature inferences have to be made about an instance whose category membership is uncertain, feature-based inductive reasoning is used to the exclusion of category-based induction. These results contrast with the observation that people can and do use category-based induction when category membership is…
-
STYLISTIC FEATURES OF ADVERTISING TEXTS OF INFORMATIVE AND COMPARATIVE TYPES
Directory of Open Access Journals (Sweden)
Poddubskaya, O.N.
2016-06-01
Full Text Available The relevance of this article is related to the fact that nowadays advertising has a very strong impact both on the consumer market, political and cultural life of society, and on the language and its development as a system. Advertising has given rise to the development of a special set of stylistic features of a text, formed under the influence of reviving advertising traditions in the Russian language and under the active impact of energetic and pushy European advertising. The purpose of this study is to explore stylistic features of informative and comparative advertising texts. The object of research is Russian-language advertising in printed media and on television. In the end of the article we made conclusions about groups of language means used for different stylistic devices in informative and comparative advertising texts. Analysis of stylistic features of modern informative and comparative advertising texts can be of great interest to specialists in the field of theoretical studies of modern advertising.
-
Directory of Open Access Journals (Sweden)
Anna Heuer
2016-08-01
Full Text Available The limited capacity of visual working memory necessitates attentional mechanisms that selectively update and maintain only the most task-relevant content. Psychophysical experiments have shown that the retroactive selection of memory content can be based on visual properties such as location or shape, but the neural basis for such differential selection is unknown. For example, it is not known if there are different cortical modules specialized for spatial versus feature-based mnemonic attention, in the same way that has been demonstrated for attention to perceptual input. Here, we used transcranial magnetic stimulation (TMS to identify areas in human parietal and occipital cortex involved in the selection of objects from memory based on cues to their location (spatial information or their shape (featural information. We found that TMS over the supramarginal gyrus (SMG selectively facilitated spatial selection, whereas TMS over the lateral occipital cortex selectively enhanced feature-based selection for remembered objects in the contralateral visual field. Thus, different cortical regions are responsible for spatial vs. feature-based selection of working memory representations. Since the same regions are involved in attention to external events, these new findings indicate overlapping mechanisms for attentional control over perceptual input and mnemonic representations.
-
Zhao, Danyang; Lustria, Mia Liza A; Hendrickse, Joshua
2017-06-01
To examine the information and communication technology (ICT) features of psychoeducational interventions for depression delivered via the Internet or via mobile technology. Web- and mobile-based psychoeducational intervention studies published from 2004 to 2014 were selected and reviewed by two independent coders. A total of 55 unique studies satisfied the selection criteria. The review revealed a diverse range of ICTs used to support the psychoeducational programs. Most interventions used websites as their main mode of delivery and reported greater use of communication tools compared to effective approaches like tailoring or interactive technologies games, videos, and self-monitoring tools. Many of the studies relied on medium levels of clinician involvement and only a few were entirely self-guided. Programs that reported higher levels of clinician involvement also reported using more communication tools, and reported greater compliance to treatment. Future experimental studies may help unpack the effects of technology features and reveal new ways to automate aspects of clinician input. There is a need to further examine ways ICTs can be optimized to reduce the burden on clinicians whilst enhancing the delivery of proven effective therapeutic approaches. Copyright © 2017 Elsevier B.V. All rights reserved.
-
Directory of Open Access Journals (Sweden)
Suzan Bakri Hassan
2015-05-01
Full Text Available The UNESCO launched a campaign #unite4heritage in Egypt to defeat extremism and intolerance. The message of such campaigne is peace, dialogue and unity embedded in cultural heritage. As culture and tourism are linked together, such message could be delivered through improving culture heritage tourism in Egypt. Islamic landmarks are considered as a part of human heritage. Therefore, the purpose of this study is to identify how much tour operators in Egypt include Islamic landmarks in their programs to determine the obstacles facing promoting cultural tourism in Islamic landmarks' areas. Additionally, the study would identify positive results in the case of developing heritage tourism in Egypt. To achieve a high result, a survey approach was employed to collect data from 100 tour operators, using a completed questionnaire technique as well as a Likert Scale and statistical models in order to test and interpret the research outcomes. The research findings indicated that although tour operators in Egypt are convinced of the significance of the Islamic landmarks, there is no contradiction between creating global understanding and at the same time achieving benefit to the local community. However, there is a range of obstacles facing promoting such type of tourism in Egypt. Keywords: Culture heritage tourism, community, Egypt, Islamic civilization.
-
Quantitative assessment of regional left ventricular motion using endocardial landmarks
C.J. Slager (Cornelis); T.E.H. Hooghoudt (Ton); P.W.J.C. Serruys (Patrick); J.C.H. Schuurbiers (Johan); J.H.C. Reiber (Johan); G.T. Meester (Geert); P.D. Verdouw (Pieter); P.G. Hugenholtz (Paul)
1986-01-01
textabstractIn this study the hypothesis is tested that the motion pattern of small anatomic landmarks, recognizable at the left ventricular endocardial border in the contrast angiocardiogram, reflects the motion of the endocardial wall. To verify this, minute metal markers were inserted in the
-
Feature Space Dimensionality Reduction for Real-Time Vision-Based Food Inspection
Directory of Open Access Journals (Sweden)
Mai Moussa CHETIMA
2009-03-01
Full Text Available Machine vision solutions are becoming a standard for quality inspection in several manufacturing industries. In the processed-food industry where the appearance attributes of the product are essential to customer’s satisfaction, visual inspection can be reliably achieved with machine vision. But such systems often involve the extraction of a larger number of features than those actually needed to ensure proper quality control, making the process less efficient and difficult to tune. This work experiments with several feature selection techniques in order to reduce the number of attributes analyzed by a real-time vision-based food inspection system. Identifying and removing as much irrelevant and redundant information as possible reduces the dimensionality of the data and allows classification algorithms to operate faster. In some cases, accuracy on classification can even be improved. Filter-based and wrapper-based feature selectors are experimentally evaluated on different bakery products to identify the best performing approaches.
-
Print Advertisements for Alzheimer’s Disease Drugs: Informational and Transformational Features
Gooblar, Jonathan; Carpenter, Brian D.
2014-01-01
Purpose We examined print advertisements for Alzheimer’s disease drugs published in journals and magazines between January 2008 and February 2012, using an informational versus transformational theoretical framework to identify objective and persuasive features. Methods In 29 unique advertisements, we used qualitative methods to code and interpret identifying information, charts, benefit and side effect language, and persuasive appeals embedded in graphics and narratives. Results Most elements contained a mixture of informational and transformational features. Charts were used infrequently, but when they did appear the accompanying text often exaggerated the data. Benefit statements covered an array of symptoms, drug properties, and caregiver issues. Side effect statements often used positive persuasive appeals. Graphics and narrative features emphasized positive emotions and outcomes. Implications We found subtle and sophisticated attempts both to educate and to persuade readers. It is important for consumers and prescribing physicians to read print advertisements critically so that they can make informed treatment choices. PMID:23687184
-
DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm
Soufan, Othman
2015-02-26
Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem\\'s dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filteringmethods thatmay be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs.
-
DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm
Soufan, Othman; Kleftogiannis, Dimitrios A.; Kalnis, Panos; Bajic, Vladimir B.
2015-01-01
Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem's dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filteringmethods thatmay be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs.
-
Multiple Information Fusion Face Ｒecognition Using Key Feature Points
Directory of Open Access Journals (Sweden)
LIN Kezheng
2017-06-01
Full Text Available After years of face recognition research，due to the effect of illumination，noise and other conditions have led to the recognition rate is relatively low，2 d face recognition technology has couldn’t keep up with the pace of The Times the forefront，Although 3 d face recognition technology is developing step by step，but it has a higher complexity. In order to solve this problem，based on the traditional depth information positioning method and local characteristic analysis methods LFA，puts forward an improved 3 d face key feature points localization algorithm， and on the basis of the trained sample which obtained by complete cluster，further put forward the global and local feature extraction algorithm of weighted fusion. Through FＲGC and BU-3DFE experiment data comparison and analysis of the two face library，the method in terms of 3 d face recognition effect has a higher robustness.
-
Unified framework for recognition, localization and mapping using wearable cameras.
Vázquez-Martín, Ricardo; Bandera, Antonio
2012-08-01
Monocular approaches to simultaneous localization and mapping (SLAM) have recently addressed with success the challenging problem of the fast computation of dense reconstructions from a single, moving camera. Thus, if these approaches initially relied on the detection of a reduced set of interest points to estimate the camera position and the map, they are currently able to reconstruct dense maps from a handheld camera while the camera coordinates are simultaneously computed. However, these maps of 3-dimensional points usually remain meaningless, that is, with no memorable items and without providing a way of encoding spatial relationships between objects and paths. In humans and mobile robotics, landmarks play a key role in the internalization of a spatial representation of an environment. They are memorable cues that can serve to define a region of the space or the location of other objects. In a topological representation of the space, landmarks can be identified and located according to its structural, perceptive or semantic significance and distinctiveness. But on the other hand, landmarks may be difficult to be located in a metric representation of the space. Restricted to the domain of visual landmarks, this work describes an approach where the map resulting from a point-based, monocular SLAM is annotated with the semantic information provided by a set of distinguished landmarks. Both features are obtained from the image. Hence, they can be linked by associating to each landmark all those point-based features that are superimposed to the landmark in a given image (key-frame). Visual landmarks will be obtained by means of an object-based, bottom-up attention mechanism, which will extract from the image a set of proto-objects. These proto-objects could not be always associated with natural objects, but they will typically constitute significant parts of these scene objects and can be appropriately annotated with semantic information. Moreover, they will be
-
Directory of Open Access Journals (Sweden)
Mosharraf R
2004-02-01
Full Text Available The determination of the dental midline is necessary in most dental procedures."nOne of the methods to fulfill this goal is to determine the facial midline based on the midpoints of the"nforehead, nose, upper lip and chin. However, for various reasons, this method has not always been"nproved successful. In such cases, different techniques, based on the investigations in the edentulous"npatients, have been suggested."nPurpose: The aim of this study was to investigate the conformity of some landmarks such as labial"nfrenum, incisive papilla and mid palatal suture with dental and facial midlines among people with natural"ndentition in order to obtain accurate anatomic landmarks for denture replacement."nMaterials and Methods: In this descriptive study, 96 dental students, having all their permanent teeth"nand without any orthognathic problem, were chosen. For each subject, Alginate impressions and dental"ncasts were prepared. Then, centric occlusion was recorded with a biting wax and the facial mid line was"ndetermined on the anterior part of it. The distances from the facial midline to the upper teeth midline,"nincisive papilla, labial frenum and mid palatal suture were determined with a special tool and were"nmeasured by a VERNIEH two times. In order to analyze the results, Chi- Square and t-student tests were"nused."nResults: The average of facial midline distance to the upper teeth midline, the labial frenum, the incisive"npapilla and the mid palatal suture were 0.83±0.60, 0.67±G.54, 0.83±00.63 and 0.81±0.62 mm,"nrespectively. There was no significant difference between males and females. Labial frenum showed the"nminimum distance to the facial midline, while the incisive papilla had the maximum. There was no"nsignificant difference between these anatomic landmarks, in conformity or unconformity with the facial"nmidline"nConclusion: Considering the low percentage of the subjects with complete conformity and the lack of
-
The urban features of informal settlements in Jakarta, Indonesia.
Alzamil, Waleed
2017-12-01
This data article contains the urban features of three informal settlements in Jakarta: A. Kampung Bandan; B. Kampung Luar Batang; And C. Kampung Muara Baru. The data describes the urban features of physical structures, infrastructures, and public services. These data include maps showing locations of these settlements, photography of urban status, and examples of urban fabric. The data are obtained from the statistical records and field surveys of three settlements cases.
-
Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review
Weal, Mark; Morrison, Leanne; Yardley, Lucy
2018-01-01
Background Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects. Objective The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social media features as part of their intervention infrastructure. A taxonomy of social media features is presented to inform the development, description, and evaluation of behavioral interventions. Methods Search terms were used in 8 databases to identify DBCIs that incorporated social media features and targeted tobacco smoking, diet and nutrition, physical activities, or alcohol consumption. The screening and review process was performed by 2 independent researchers. Results A total of 5264 articles were screened, and 143 articles describing a total of 134 studies were retained for full review. The majority of studies (70%) reported positive outcomes, followed by 28% finding no effects with regard to their respective objectives and hypothesis, and 2% of the studies found that their interventions had negative outcomes. Few studies reported on the association between the inclusion of social media features and intervention effect. A taxonomy of social media features used in behavioral interventions has been presented with 36 social media features organized under 7 high-level categories. The taxonomy has been used to guide the analysis of this review. Conclusions Although social media features are commonly included in DBCIs, there is an acute lack of information with respect to their effect on outcomes and a lack of clear guidance to inform the selection process based on the features’ suitability for the different behaviors. The proposed taxonomy along with the set of recommendations included
-
Farran, E. K.; Formby, S.; Daniyal, F.; Holmes, T.; Van Herwegen, J.
2016-01-01
Background: Successful navigation is crucial to everyday life. Individuals with Williams syndrome (WS) have impaired spatial abilities. This includes a deficit in spatial navigation abilities such as learning the route from A to B. To-date, to determine whether participants attend to landmarks when learning a route, landmark recall tasks have been…
-
EEG feature selection method based on decision tree.
Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun
2015-01-01
This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.
-
Spering, Miriam; Carrasco, Marisa
2012-01-01
Feature-based attention enhances visual processing and improves perception, even for visual features that we are not aware of. Does feature-based attention also modulate motor behavior in response to visual information that does or does not reach awareness? Here we compare the effect of feature-based attention on motion perception and smooth pursuit eye movements in response to moving dichoptic plaids–stimuli composed of two orthogonally-drifting gratings, presented separately to each eye–in ...
-
Visual navigation in insects: coupling of egocentric and geocentric information
Wehner; Michel; Antonsen
1996-01-01
Social hymenopterans such as bees and ants are central-place foragers; they regularly depart from and return to fixed positions in their environment. In returning to the starting point of their foraging excursion or to any other point, they could resort to two fundamentally different ways of navigation by using either egocentric or geocentric systems of reference. In the first case, they would rely on information continuously collected en route (path integration, dead reckoning), i.e. integrate all angles steered and all distances covered into a mean home vector. In the second case, they are expected, at least by some authors, to use a map-based system of navigation, i.e. to obtain positional information by virtue of the spatial position they occupy within a larger environmental framework. In bees and ants, path integration employing a skylight compass is the predominant mechanism of navigation, but geocentred landmark-based information is used as well. This information is obtained while the animal is dead-reckoning and, hence, added to the vector course. For example, the image of the horizon skyline surrounding the nest entrance is retinotopically stored while the animal approaches the goal along its vector course. As shown in desert ants (genus Cataglyphis), there is neither interocular nor intraocular transfer of landmark information. Furthermore, this retinotopically fixed, and hence egocentred, neural snapshot is linked to an external (geocentred) system of reference. In this way, geocentred information might more and more complement and potentially even supersede the egocentred information provided by the path-integration system. In competition experiments, however, Cataglyphis never frees itself of its homeward-bound vector - its safety-line, so to speak - by which it is always linked to home. Vector information can also be transferred to a longer-lasting (higher-order) memory. There is no need to invoke the concept of the mental analogue of a topographic
-
Deformable Image Registration with Inclusion of Autodetected Homologous Tissue Features
Directory of Open Access Journals (Sweden)
Qingsong Zhu
2012-01-01
Full Text Available A novel deformable registration algorithm is proposed in the application of radiation therapy. The algorithm starts with autodetection of a number of points with distinct tissue features. The feature points are then matched by using the scale invariance features transform (SIFT method. The associated feature point pairs are served as landmarks for the subsequent thin plate spline (TPS interpolation. Several registration experiments using both digital phantom and clinical data demonstrate the accuracy and efficiency of the method. For the 3D phantom case, markers with error less than 2 mm are over 85% of total test markers, and it takes only 2-3 minutes for 3D feature points association. The proposed method provides a clinically practical solution and should be valuable for various image-guided radiation therapy (IGRT applications.
-
Thermal-depth matching in dynamic scene based on affine projection and feature registration
Wang, Hongyu; Jia, Tong; Wu, Chengdong; Li, Yongqiang
2018-03-01
This paper aims to study the construction of 3D temperature distribution reconstruction system based on depth and thermal infrared information. Initially, a traditional calibration method cannot be directly used, because the depth and thermal infrared camera is not sensitive to the color calibration board. Therefore, this paper aims to design a depth and thermal infrared camera calibration board to complete the calibration of the depth and thermal infrared camera. Meanwhile a local feature descriptors in thermal and depth images is proposed. The belief propagation matching algorithm is also investigated based on the space affine transformation matching and local feature matching. The 3D temperature distribution model is built based on the matching of 3D point cloud and 2D thermal infrared information. Experimental results show that the method can accurately construct the 3D temperature distribution model, and has strong robustness.
-
Matsukura, Michi; Vecera, Shaun P
2011-02-01
Attention selects objects as well as locations. When attention selects an object's features, observers identify two features from a single object more accurately than two features from two different objects (object-based effect of attention; e.g., Duncan, Journal of Experimental Psychology: General, 113, 501-517, 1984). Several studies have demonstrated that object-based attention can operate at a late visual processing stage that is independent of objects' spatial information (Awh, Dhaliwal, Christensen, & Matsukura, Psychological Science, 12, 329-334, 2001; Matsukura & Vecera, Psychonomic Bulletin & Review, 16, 529-536, 2009; Vecera, Journal of Experimental Psychology: General, 126, 14-18, 1997; Vecera & Farah, Journal of Experimental Psychology: General, 123, 146-160, 1994). In the present study, we asked two questions regarding this late object-based selection mechanism. In Part I, we investigated how observers' foreknowledge of to-be-reported features allows attention to select objects, as opposed to individual features. Using a feature-report task, a significant object-based effect was observed when to-be-reported features were known in advance but not when this advance knowledge was absent. In Part II, we examined what drives attention to select objects rather than individual features in the absence of observers' foreknowledge of to-be-reported features. Results suggested that, when there was no opportunity for observers to direct their attention to objects that possess to-be-reported features at the time of stimulus presentation, these stimuli must retain strong perceptual cues to establish themselves as separate objects.
-
Forebrain development in fetal MRI: evaluation of anatomical landmarks before gestational week 27
International Nuclear Information System (INIS)
Schmook, Maria T.; Weber, Michael; Kasprian, Gregor; Nemec, Stefan; Prayer, Daniela; Brugger, Peter C.; Krampl-Bettelheim, Elisabeth
2010-01-01
Forebrain malformations include some of the most severe developmental anomalies and require early diagnosis. The proof of normal or abnormal prosencephalic development may have an influence on further management in the event of a suspected fetal malformation. The purpose of this retrospective study was to evaluate the detectability of anatomical landmarks of forebrain development using in vivo fetal magnetic resonance imaging (MRI) before gestational week (gw) 27. MRI studies of 83 singleton fetuses (gw 16-26, average ±sd: gw 22 ± 2) performed at 1.5 Tesla were assessed. T2-weighted (w) fast spin echo, T1w gradient-echo and diffusion-weighted sequences were screened for the detectability of anatomical landmarks as listed below. The interhemispheric fissure, ocular bulbs, corpus callosum, infundibulum, chiasm, septum pellucidum (SP), profile, and palate were detectable in 95%, 95%, 89%, 87%, 82%, 81%, 78%, 78% of cases. Olfactory tracts were more easily delineated than bulbs and sulci (37% versus 18% and 8%), with significantly higher detection rates in the coronal plane. The pituitary gland could be detected on T1w images in 60% with an increasing diameter with gestational age (p=0.041). The delineation of olfactory tracts (coronal plane), chiasm, SP and pituitary gland were significantly increased after week 21 (p<0.05). Pathologies were found in 28% of cases. This study provides detection rates for anatomical landmarks of forebrain development with fetal MRI before gw 27. Several anatomical structures are readily detectable with routine fetal MRI sequences; thus, if these landmarks are not delineable, it should raise the suspicion of a pathology. Recommendations regarding favorable sequences/planes are provided. (orig.)
-
Forebrain development in fetal MRI: evaluation of anatomical landmarks before gestational week 27
Energy Technology Data Exchange (ETDEWEB)
Schmook, Maria T.; Weber, Michael; Kasprian, Gregor; Nemec, Stefan; Prayer, Daniela [Medical University of Vienna, Department of Radiology/Division of Neuro- and Musculoskeletal Radiology, Vienna (Austria); Brugger, Peter C. [Medical University of Vienna, Integrative Morphology Group, Center for Anatomy and Cell Biology, Vienna (Austria); Krampl-Bettelheim, Elisabeth [Department of Obstetrics and Gynecology / Division of Obstetrics and Feto-maternal Medicine, Vienna (Austria)
2010-06-15
Forebrain malformations include some of the most severe developmental anomalies and require early diagnosis. The proof of normal or abnormal prosencephalic development may have an influence on further management in the event of a suspected fetal malformation. The purpose of this retrospective study was to evaluate the detectability of anatomical landmarks of forebrain development using in vivo fetal magnetic resonance imaging (MRI) before gestational week (gw) 27. MRI studies of 83 singleton fetuses (gw 16-26, average {+-}sd: gw 22 {+-} 2) performed at 1.5 Tesla were assessed. T2-weighted (w) fast spin echo, T1w gradient-echo and diffusion-weighted sequences were screened for the detectability of anatomical landmarks as listed below. The interhemispheric fissure, ocular bulbs, corpus callosum, infundibulum, chiasm, septum pellucidum (SP), profile, and palate were detectable in 95%, 95%, 89%, 87%, 82%, 81%, 78%, 78% of cases. Olfactory tracts were more easily delineated than bulbs and sulci (37% versus 18% and 8%), with significantly higher detection rates in the coronal plane. The pituitary gland could be detected on T1w images in 60% with an increasing diameter with gestational age (p=0.041). The delineation of olfactory tracts (coronal plane), chiasm, SP and pituitary gland were significantly increased after week 21 (p<0.05). Pathologies were found in 28% of cases. This study provides detection rates for anatomical landmarks of forebrain development with fetal MRI before gw 27. Several anatomical structures are readily detectable with routine fetal MRI sequences; thus, if these landmarks are not delineable, it should raise the suspicion of a pathology. Recommendations regarding favorable sequences/planes are provided. (orig.)
-
Directory of Open Access Journals (Sweden)
Branislava Gemovic
2013-01-01
Full Text Available There are more than 500 amino acid substitutions in each human genome, and bioinformatics tools irreplaceably contribute to determination of their functional effects. We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. The new algorithm is based on the informational spectrum method (ISM, a feature-based technique, and statistical analysis. Our dataset contained neutral polymorphisms and mutations associated with myeloid malignancies from epigenetic regulators ASXL1, DNMT3A, EZH2, and TET2. PolyPhen-2 and SIFT had significantly lower accuracies in predicting the effects of amino acid substitutions outside CFDs than expected, with especially low sensitivity. On the other hand, only ISM algorithm showed statistically significant classification of these sequences. It outperformed PolyPhen-2 and SIFT by 15% and 13%, respectively. These results suggest that feature-based methods, like ISM, are more suitable for the classification of amino acid substitutions outside CFDs than phylogeny-based tools.
-
[Lymphoscintigrams with anatomical landmarks obtained with vector graphics].
Rubini, Giuseppe; Antonica, Filippo; Renna, Maria Antonia; Ferrari, Cristina; Iuele, Francesca; Stabile Ianora, Antonio Amato; Losco, Matteo; Niccoli Asabella, Artor
2012-11-01
Nuclear medicine images are difficult to interpret because they do not include anatomical details. The aim of this study was to obtain lymphoscintigrams with anatomical landmarks that could be easily interpreted by General Physicians. Traditional lymphoscintigrams were processed with Adobe© Photoshop® CS6 and converted into vector images created by Illustrator®. The combination with a silhouette vector improved image interpretation, without resulting in longer radiation exposure or acquisition times.
-
The Research and Application of SURF Algorithm Based on Feature Point Selection Algorithm
Directory of Open Access Journals (Sweden)
Zhang Fang Hu
2014-04-01
Full Text Available As the pixel information of depth image is derived from the distance information, when implementing SURF algorithm with KINECT sensor for static sign language recognition, there can be some mismatched pairs in palm area. This paper proposes a feature point selection algorithm, by filtering the SURF feature points step by step based on the number of feature points within adaptive radius r and the distance between the two points, it not only greatly improves the recognition rate, but also ensures the robustness under the environmental factors, such as skin color, illumination intensity, complex background, angle and scale changes. The experiment results show that the improved SURF algorithm can effectively improve the recognition rate, has a good robustness.
-
An Adaptive Algorithm for Finding Frequent Sets in Landmark Windows
DEFF Research Database (Denmark)
Dang, Xuan-Hong; Ong, Kok-Leong; Lee, Vincent
2012-01-01
We consider a CPU constrained environment for finding approximation of frequent sets in data streams using the landmark window. Our algorithm can detect overload situations, i.e., breaching the CPU capacity, and sheds data in the stream to “keep up”. This is done within a controlled error threshold...
-
Daluisio, Stephen C.
2014-01-01
In the late 1980s, the Eastman Kodak company initiated what would become one of the biggest trends in information technology (IT): outsourcing. IT outsourcing (ITO) allows a company to focus on the services that will differentiate it from its competitors and farm out nondifferentiating services. ITO has grown from the initial landmark effort at…
-
Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.
2008-01-01
A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.
-
Zhang, Dongqing; Liu, Yuan; Noble, Jack H.; Dawant, Benoit M.
2016-03-01
Cochlear Implants (CIs) are electrode arrays that are surgically inserted into the cochlea. Individual contacts stimulate frequency-mapped nerve endings thus replacing the natural electro-mechanical transduction mechanism. CIs are programmed post-operatively by audiologists but this is currently done using behavioral tests without imaging information that permits relating electrode position to inner ear anatomy. We have recently developed a series of image processing steps that permit the segmentation of the inner ear anatomy and the localization of individual contacts. We have proposed a new programming strategy that uses this information and we have shown in a study with 68 participants that 78% of long term recipients preferred the programming parameters determined with this new strategy. A limiting factor to the large scale evaluation and deployment of our technique is the amount of user interaction still required in some of the steps used in our sequence of image processing algorithms. One such step is the rough registration of an atlas to target volumes prior to the use of automated intensity-based algorithms when the target volumes have very different fields of view and orientations. In this paper we propose a solution to this problem. It relies on a random forest-based approach to automatically localize a series of landmarks. Our results obtained from 83 images with 132 registration tasks show that automatic initialization of an intensity-based algorithm proves to be a reliable technique to replace the manual step.
-
Feature-Based Analysis of Plasma-Based Particle Acceleration Data
Energy Technology Data Exchange (ETDEWEB)
Rubel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Geddes, Cameron G. R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chen, Min [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Cormier-Michel, Estelle [Tech-X Corp., Boulder, CO (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2014-02-01
Plasma-based particle accelerators can produce and sustain thousands of times stronger acceleration fields than conventional particle accelerators, providing a potential solution to the problem of the growing size and cost of conventional particle accelerators. To facilitate scientific knowledge discovery from the ever growing collections of accelerator simulation data generated by accelerator physicists to investigate next-generation plasma-based particle accelerator designs, we describe a novel approach for automatic detection and classification of particle beams and beam substructures due to temporal differences in the acceleration process, here called acceleration features. The automatic feature detection in combination with a novel visualization tool for fast, intuitive, query-based exploration of acceleration features enables an effective top-down data exploration process, starting from a high-level, feature-based view down to the level of individual particles. We describe the application of our analysis in practice to analyze simulations of single pulse and dual and triple colliding pulse accelerator designs, and to study the formation and evolution of particle beams, to compare substructures of a beam and to investigate transverse particle loss.
-
A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images
Directory of Open Access Journals (Sweden)
Zhiying Song
2017-01-01
Full Text Available The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS method and a dynamic threshold denoising (DTD method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933 on feature images and less Euclidean distance error (ED = 2.826 on landmark points, outperforming the source data (NC = −0.496, ED = 25.847 and the compared method (NC = −0.614, ED = 16.085. Moreover, our method is about ten times faster than the compared one.
-
A malware detection scheme based on mining format information.
Bai, Jinrong; Wang, Junfeng; Zou, Guozhong
2014-01-01
Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. In this paper, we proposed a malware detection approach by mining format information of PE (portable executable) files. Based on in-depth analysis of the static format information of the PE files, we extracted 197 features from format information of PE files and applied feature selection methods to reduce the dimensionality of the features and achieve acceptable high performance. When the selected features were trained using classification algorithms, the results of our experiments indicate that the accuracy of the top classification algorithm is 99.1% and the value of the AUC is 0.998. We designed three experiments to evaluate the performance of our detection scheme and the ability of detecting unknown and new malware. Although the experimental results of identifying new malware are not perfect, our method is still able to identify 97.6% of new malware with 1.3% false positive rates.
-
Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.
Elaheebocus, Sheik Mohammad Roushdat Ally; Weal, Mark; Morrison, Leanne; Yardley, Lucy
2018-02-22
Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects. The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social media features as part of their intervention infrastructure. A taxonomy of social media features is presented to inform the development, description, and evaluation of behavioral interventions. Search terms were used in 8 databases to identify DBCIs that incorporated social media features and targeted tobacco smoking, diet and nutrition, physical activities, or alcohol consumption. The screening and review process was performed by 2 independent researchers. A total of 5264 articles were screened, and 143 articles describing a total of 134 studies were retained for full review. The majority of studies (70%) reported positive outcomes, followed by 28% finding no effects with regard to their respective objectives and hypothesis, and 2% of the studies found that their interventions had negative outcomes. Few studies reported on the association between the inclusion of social media features and intervention effect. A taxonomy of social media features used in behavioral interventions has been presented with 36 social media features organized under 7 high-level categories. The taxonomy has been used to guide the analysis of this review. Although social media features are commonly included in DBCIs, there is an acute lack of information with respect to their effect on outcomes and a lack of clear guidance to inform the selection process based on the features' suitability for the different behaviors. The proposed taxonomy along with the set of recommendations included in this review will support future research aimed
-
Buser, Thaddaeus J; Sidlauskas, Brian L; Summers, Adam P
2018-05-01
We contrast 2D vs. 3D landmark-based geometric morphometrics in the fish subfamily Oligocottinae by using 3D landmarks from CT-generated models and comparing the morphospace of the 3D landmarks to one based on 2D landmarks from images. The 2D and 3D shape variables capture common patterns across taxa, such that the pairwise Procrustes distances among taxa correspond and the trends captured by principal component analysis are similar in the xy plane. We use the two sets of landmarks to test several ecomorphological hypotheses from the literature. Both 2D and 3D data reject the hypothesis that head shape correlates significantly with the depth at which a species is commonly found. However, in taxa where shape variation in the z-axis is high, the 2D shape variables show sufficiently strong distortion to influence the outcome of the hypothesis tests regarding the relationship between mouth size and feeding ecology. Only the 3D data support previous studies which showed that large mouth sizes correlate positively with high percentages of elusive prey in the diet. When used to test for morphological divergence, 3D data show no evidence of divergence, while 2D data show that one clade of oligocottines has diverged from all others. This clade shows the greatest degree of z-axis body depth within Oligocottinae, and we conclude that the inability of the 2D approach to capture this lateral body depth causes the incongruence between 2D and 3D analyses. Anat Rec, 301:806-818, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
-
A NEW STRATEGY FOR IMPROVING FEATURE SETS IN A DISCRETE HMMBASED HANDWRITING RECOGNITION SYSTEM
Grandidier, F.; Sabourin, R.; Suen, C.Y.; Gilloux, M.
2004-01-01
In this paper we introduce a new strategy for improving a discrete HMMbased handwriting recognition system, by integrating several information sources from specialized feature sets. For a given system, the basic idea is to keep the most discriminative features, and to replace the others with new
-
A CNN-Based Fusion Method for Feature Extraction from Sentinel Data
Directory of Open Access Journals (Sweden)
Giuseppe Scarpa
2018-02-01
Full Text Available Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. A possible alternative is to benefit from weather-insensitive synthetic aperture radar (SAR images. In many real-world applications, critical decisions are made based on some informative optical or radar features related to items such as water, vegetation or soil. Under cloudy conditions, however, optical-based features are not available, and they are commonly reconstructed through linear interpolation between data available at temporally-close time instants. In this work, we propose to estimate missing optical features through data fusion and deep-learning. Several sources of information are taken into account—optical sequences, SAR sequences, digital elevation model—so as to exploit both temporal and cross-sensor dependencies. Based on these data and a tiny cloud-free fraction of the target image, a compact convolutional neural network (CNN is trained to perform the desired estimation. To validate the proposed approach, we focus on the estimation of the normalized difference vegetation index (NDVI, using coupled Sentinel-1 and Sentinel-2 time-series acquired over an agricultural region of Burkina Faso from May–November 2016. Several fusion schemes are considered, causal and non-causal, single-sensor or joint-sensor, corresponding to different operating conditions. Experimental results are very promising, showing a significant gain over baseline methods according to all performance indicators.
-
Robust and Effective Component-based Banknote Recognition by SURF Features.
Hasanuzzaman, Faiz M; Yang, Xiaodong; Tian, YingLi
2011-01-01
Camera-based computer vision technology is able to assist visually impaired people to automatically recognize banknotes. A good banknote recognition algorithm for blind or visually impaired people should have the following features: 1) 100% accuracy, and 2) robustness to various conditions in different environments and occlusions. Most existing algorithms of banknote recognition are limited to work for restricted conditions. In this paper we propose a component-based framework for banknote recognition by using Speeded Up Robust Features (SURF). The component-based framework is effective in collecting more class-specific information and robust in dealing with partial occlusion and viewpoint changes. Furthermore, the evaluation of SURF demonstrates its effectiveness in handling background noise, image rotation, scale, and illumination changes. To authenticate the robustness and generalizability of the proposed approach, we have collected a large dataset of banknotes from a variety of conditions including occlusion, cluttered background, rotation, and changes of illumination, scaling, and viewpoints. The proposed algorithm achieves 100% recognition rate on our challenging dataset.
-
a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image
Li, L.; Yang, H.; Chen, Q.; Liu, X.
2018-04-01
Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.
-
Feature-based Alignment of Volumetric Multi-modal Images
Toews, Matthew; Zöllei, Lilla; Wells, William M.
2014-01-01
This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955
-
Landmarks for Sacral Debridement in Sacral Pressure Sores.
Choo, Joshua H; Wilhelmi, Bradon J
2016-03-01
Most cases of sacral osteomyelitis arising in the setting of sacral pressure ulcers require minimal cortical debridement. When faced with advanced bony involvement, the surgeon is often unclear about how much can safely be resected. Unfamiliarity with sacral anatomy can lead to concerns of inadvertent entry into the dural space and compromise of future flap options. A cadaveric study (n = 6), in which a wide posterior dissection of the sacrum, was performed. Relationships of the dural sac to bony landmarks of the posterior pelvis were noted. The termination of the dural sac was found in our study to occur at the junction of S2/S3 vertebral bodies, which was located at a mean distance of 0.38 ± 0.16 cm distal to the inferior-most extent of the posterior superior iliac spine (PSIS). The mean thickness of the posterior table of sacrum at this level was 1.7 cm at the midline and 0.5 cm at the sacral foramina. The PSIS is a reliable landmark for localizing the S2/S3 junction and the termination of the dural sac. Sacral debridement medial to the sacral foramina above the level of PSIS must be conservative whenever possible. If aggressive debridement is necessary above this level, the surgeon must be alert to the possibility of dural involvement.
-
GRAMMAR RULE BASED INFORMATION RETRIEVAL MODEL FOR BIG DATA
Directory of Open Access Journals (Sweden)
T. Nadana Ravishankar
2015-07-01
Full Text Available Though Information Retrieval (IR in big data has been an active field of research for past few years; the popularity of the native languages presents a unique challenge in big data information retrieval systems. There is a need to retrieve information which is present in English and display it in the native language for users. This aim of cross language information retrieval is complicated by unique features of the native languages such as: morphology, compound word formations, word spelling variations, ambiguity, word synonym, other language influence and etc. To overcome some of these issues, the native language is modeled using a grammar rule based approach in this work. The advantage of this approach is that the native language is modeled and its unique features are encoded using a set of inference rules. This rule base coupled with the customized ontological system shows considerable potential and is found to show better precision and recall.
-
Gilchrist, Amanda L; Duarte, Audrey; Verhaeghen, Paul
2016-01-01
Research with younger adults has shown that retrospective cues can be used to orient top-down attention toward relevant items in working memory. We examined whether older adults could take advantage of these cues to improve memory performance. Younger and older adults were presented with visual arrays of five colored shapes; during maintenance, participants were presented either with an informative cue based on an object feature (here, object shape or color) that would be probed, or with an uninformative, neutral cue. Although older adults were less accurate overall, both age groups benefited from the presentation of an informative, feature-based cue relative to a neutral cue. Surprisingly, we also observed differences in the effectiveness of shape versus color cues and their effects upon post-cue memory load. These results suggest that older adults can use top-down attention to remove irrelevant items from visual working memory, provided that task-relevant features function as cues.
-
3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.
Zhong, Zichun; Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun; Mao, Weihua
2016-01-01
By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.
-
3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
Directory of Open Access Journals (Sweden)
Zichun Zhong
2016-01-01
Full Text Available By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes.
-
Corrective surgery for canine patellar luxation in 75 cases (107 limbs: landmark for block recession
Directory of Open Access Journals (Sweden)
Mitsuhiro Isaka
2014-05-01
Full Text Available Canine medial patellar luxation (MPL is a very common orthopedic disease in small animals. Because the pathophysiology of this disease involves various pathways, the surgical techniques and results vary according to the veterinarian. Further, the landmark for block recession is not completely clear. We retrospectively evaluated 75 dogs (107 limbs with MPL in whom our landmark for block recession was used from July 2008 to May 2013. Information regarding the breed, age, sex, body weight, body condition score (BCS, lateral vs bilateral, pre-operative grading, surgical techniques, removal of implants, concomitance with anterior cruciate ligament (ACL rupture, re-luxation, re-operation, and rehabilitation was obtained from the medical records. The breeds were as follows: Chihuahua (n=23, Pomeranian (n=12, Yorkshire Terrier (n=9, and so on. The study group consisted of 33 males (castrated n=13 and 42 females (spayed n=21. The median age was 53.3±35.9 months (32-146 months; 13 cases were less than 12 months of age (17.3%. The pre-surgical BCSs were as follows: 1 (n=0, 2 (n=20, 3 (n=24, 4 (n=24 and 5 (n=7. The body weight was 4.51±3.48 kg (1.34-23.0 kg; 71 cases (94.7% were less than 10 kg. The MPL grades (each limb were G1 (n=1, G2 (n=18, G3 (n=78, and G4 (n=10; 32 cases were bilateral and 43 cases were unilateral (right n=27; left n=16. The specific surgical procedure (distal femoral osteotomy was 3 stifles in Chihuahuas. Concurrent with ACL rupture was 16/107 stifles (15.0% corrected with the over-the-top method or the extracapsular method in Papillons (5/6, Chihuahuas (5/23, and so on. The occurrences of re-luxation and re-operation were 3 out of 107 stifles (2.8% and 0%, respectively. In this retrospective study, we present a potentially good surgical landmark for block recession of MPL in dogs.
-
Processing of word stress related acoustic information: A multi-feature MMN study.
Honbolygó, Ferenc; Kolozsvári, Orsolya; Csépe, Valéria
2017-08-01
In the present study, we investigated the processing of word stress related acoustic features in a word context. In a passive oddball multi-feature MMN experiment, we presented a disyllabic pseudo-word with two acoustically similar syllables as standard stimulus, and five contrasting deviants that differed from the standard in that they were either stressed on the first syllable or contained a vowel change. Stress was realized by an increase of f0, intensity, vowel duration or consonant duration. The vowel change was used to investigate if phonemic and prosodic changes elicit different MMN components. As a control condition, we presented non-speech counterparts of the speech stimuli. Results showed all but one feature (non-speech intensity deviant) eliciting the MMN component, which was larger for speech compared to non-speech stimuli. Two other components showed stimulus related effects: the N350 and the LDN (Late Discriminative Negativity). The N350 appeared to the vowel duration and consonant duration deviants, specifically to features related to the temporal characteristics of stimuli, while the LDN was present for all features, and it was larger for speech than for non-speech stimuli. We also found that the f0 and consonant duration features elicited a larger MMN than other features. These results suggest that stress as a phonological feature is processed based on long-term representations, and listeners show a specific sensitivity to segmental and suprasegmental cues signaling the prosodic boundaries of words. These findings support a two-stage model in the perception of stress and phoneme related acoustical information. Copyright © 2017 Elsevier B.V. All rights reserved.
-
Information Commons Features Cutting-Edge Conservation and Technology
Gilroy, Marilyn
2011-01-01
This article features Richard J. Klarchek Information Commons (IC) at Loyola University Chicago, an all-glass library building on the shore of Chicago's Lake Michigan that is not only a state-of-the-art digital research library and study space--it also runs on cutting-edge energy technology. The building has attracted attention and visitors from…
-
Llewellyn, Sue; Hobson, J Allan
2015-07-01
This article argues both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep contribute to overnight episodic memory processes but their roles differ. Episodic memory may have evolved from memory for spatial navigation in animals and humans. Equally, mnemonic navigation in world and mental space may rely on fundamentally equivalent processes. Consequently, the basic spatial network characteristics of pathways which meet at omnidirectional nodes or junctions may be conserved in episodic brain networks. A pathway is formally identified with the unidirectional, sequential phases of an episodic memory. In contrast, the function of omnidirectional junctions is not well understood. In evolutionary terms, both animals and early humans undertook tours to a series of landmark junctions, to take advantage of resources (food, water and shelter), whilst trying to avoid predators. Such tours required memory for emotionally significant landmark resource-place-danger associations and the spatial relationships amongst these landmarks. In consequence, these tours may have driven the evolution of both spatial and episodic memory. The environment is dynamic. Resource-place associations are liable to shift and new resource-rich landmarks may be discovered, these changes may require re-wiring in neural networks. To realise these changes, REM may perform an associative, emotional encoding function between memory networks, engendering an omnidirectional landmark junction which is instantiated in the cortex during NREM Stage 2. In sum, REM may preplay associated elements of past episodes (rather than replay individual episodes), to engender an unconscious representation which can be used by the animal on approach to a landmark junction in wake. Copyright © 2015 Elsevier Inc. All rights reserved.
-
Directory of Open Access Journals (Sweden)
Nantian Huang
2016-09-01
Full Text Available The prediction accuracy of short-term load forecast (STLF depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original feature set was used to train an RF as the original model. After the training process, the prediction error of the original model on the test set was recorded and the permutation importance (PI value of each feature was obtained. Then, an improved sequential backward search method was used to select the optimal forecasting feature subset based on the PI value of each feature. Finally, the optimal forecasting feature subset was used to train a new RF model as the final prediction model. Experiments showed that the prediction accuracy of RF trained by the optimal forecasting feature subset was higher than that of the original model and comparative models based on support vector regression and artificial neural network.
-
Student acceptance of e-books: A case study of landmark university ...
African Journals Online (AJOL)
Student acceptance of e-books was tested using UTAUT model. Performance expectancy Effort expectancy and Facilitating conditions were seen to significantly influence the acceptance of e-books by students in Landmark University, while Social Influence did not influence acceptance of e-books. Key Words: E-books, ...
-
Color Texture Image Retrieval Based on Local Extrema Features and Riemannian Distance
Directory of Open Access Journals (Sweden)
Minh-Tan Pham
2017-10-01
Full Text Available A novel efficient method for content-based image retrieval (CBIR is developed in this paper using both texture and color features. Our motivation is to represent and characterize an input image by a set of local descriptors extracted from characteristic points (i.e., keypoints within the image. Then, dissimilarity measure between images is calculated based on the geometric distance between the topological feature spaces (i.e., manifolds formed by the sets of local descriptors generated from each image of the database. In this work, we propose to extract and use the local extrema pixels as our feature points. Then, the so-called local extrema-based descriptor (LED is generated for each keypoint by integrating all color, spatial as well as gradient information captured by its nearest local extrema. Hence, each image is encoded by an LED feature point cloud and Riemannian distances between these point clouds enable us to tackle CBIR. Experiments performed on several color texture databases including Vistex, STex, color Brodazt, USPtex and Outex TC-00013 using the proposed approach provide very efficient and competitive results compared to the state-of-the-art methods.
-
CULTURAL FEATURES SHARED BY INFORMATION SYSTEMS USERS
Directory of Open Access Journals (Sweden)
Marilena Maldonado
2006-11-01
Full Text Available Problems may arise when organizational culture is not considered in the development of information systems, such as difficulties in system implementation, since users do not accept changes in their work cultures. However, current methodology designs do not contemplate cultural factors. The objective of this investigation was to identify the main cultural features shared by the users of information systems in an Argentinean university. As result of this work it was possible to identify the memes shared by the members of the community selected, and to categorize such memes according to their incidence grade. This work seeks to be an initial step towards the construction of systems that evolve along with the organizational culture they are an integral part of.
-
Facial expression recognition under partial occlusion based on fusion of global and local features
Wang, Xiaohua; Xia, Chen; Hu, Min; Ren, Fuji
2018-04-01
Facial expression recognition under partial occlusion is a challenging research. This paper proposes a novel framework for facial expression recognition under occlusion by fusing the global and local features. In global aspect, first, information entropy are employed to locate the occluded region. Second, principal Component Analysis (PCA) method is adopted to reconstruct the occlusion region of image. After that, a replace strategy is applied to reconstruct image by replacing the occluded region with the corresponding region of the best matched image in training set, Pyramid Weber Local Descriptor (PWLD) feature is then extracted. At last, the outputs of SVM are fitted to the probabilities of the target class by using sigmoid function. For the local aspect, an overlapping block-based method is adopted to extract WLD features, and each block is weighted adaptively by information entropy, Chi-square distance and similar block summation methods are then applied to obtain the probabilities which emotion belongs to. Finally, fusion at the decision level is employed for the data fusion of the global and local features based on Dempster-Shafer theory of evidence. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the effectiveness and fault tolerance of this method.
-
Biometric features and privacy : condemned, based upon your finger print
Bullee, Jan-Willem; Veldhuis, Raymond N.J.
What information is available in biometric features besides that needed for the biometric recognition process? What if a biometric feature contains Personally Identifiable Information? Will the whole biometric system become a threat to privacy? This paper is an attempt to quantifiy the link between
-
A Method of Rotating Machinery Fault Diagnosis Based on the Close Degree of Information Entropy
Institute of Scientific and Technical Information of China (English)
GENG Jun-bao; HUANG Shu-hong; JIN Jia-shan; CHEN Fei; LIU Wei
2006-01-01
This paper presents a method of rotating machinery fault diagnosis based on the close degree of information entropy. In the view of the information entropy, we introduce four information entropy features of the rotating machinery, which describe the vibration condition of the machinery. The four features are, respectively, denominated as singular spectrum entropy, power spectrum entropy, wavelet space state feature entropy and wavelet power spectrum entropy. The value scopes of the four information entropy features of the rotating machinery in some typical fault conditions are gained by experiments, which can be acted as the standard features of fault diagnosis. According to the principle of the shorter distance between the more similar models, the decision-making method based on the close degree of information entropy is put forward to deal with the recognition of fault patterns. We demonstrate the effectiveness of this approach in an instance involving the fault pattern recognition of some rotating machinery.
-
Cloud field classification based on textural features
Sengupta, Sailes Kumar
1989-01-01
An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes
-
Energy Technology Data Exchange (ETDEWEB)
Buck, Florian M. [Veterans Administration Medical Center, Department of Radiology, San Diego, CA (United States); Institut fuer Diagnostische Radiologie, Uniklinik Balgrist, Zurich (Switzerland); Zoner, Cristiane S.; Cardoso, Fabiano; Gheno, Ramon; Nico, Marcelo A.C.; Trudell, Debra J.; Resnick, Donald [Veterans Administration Medical Center, Department of Radiology, San Diego, CA (United States); Randall, Tori D. [San Diego Museum of Man, Physical Anthropology, San Diego, CA (United States)
2010-09-15
To describe osseous landmarks that allow identification of the attachments of the ligaments and tendons in the distal medial aspect of the humerus. Reliable osseous landmarks in the distal medial aspect of the humerus were identified in 34 well-preserved specimens from a paleopathologic collection. These osseous landmarks were then sought in magnetic resonance (MR) images of ten cadaveric elbow specimens so that the ease of their visualization and optimal imaging plane could be assessed. To assign these osseous landmarks to specific attachments of the tendons and ligaments in the distal medial humerus, we cut the specimens in slices and photographed and examined them. Subsequently, the prevalence of these osseous landmarks as well as the attachment sites of the tendons and ligaments in this location was determined. We determined ten reliable osseous landmarks in the distal medial aspect of the humerus, their prevalence and ease of identification, and their relationship to the attachments of the tendons and ligaments at the medial distal humerus. It is possible to use osseous landmarks at the distal medial humerus to facilitate identification of the different attachments of tendons and ligaments when MR images of the elbow are assessed. (orig.)
-
Illusionary Inclusion--What Went Wrong with New Labour's Landmark Educational Policy?
Hodkinson, Alan
2012-01-01
This article examines the emergence and evolution of New Labour's landmark educational policy; namely that of inclusion. The author, Alan Hodkinson, associate professor at the Centre for Cultural and Disability Studies at Liverpool Hope University, illuminates his conceptual difficulties in attempting to define what inclusion was and what…
-
Object tracking system using a VSW algorithm based on color and point features
Directory of Open Access Journals (Sweden)
Lim Hye-Youn
2011-01-01
Full Text Available Abstract An object tracking system using a variable search window (VSW algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects; however, a disadvantage is that it is sensitive to non-specific color objects due to illumination and noise. Therefore, to offset this weakness, it presents the VSW algorithm based on robust feature points for the accurate tracking of moving objects. The proposed method extracts the feature points of a detected object which is the region of interest (ROI, and generates a VSW using the given information which is the positions of extracted feature points. The goal of this paper is to achieve an efficient and effective object tracking system that meets the accurate tracking of moving objects. Through experiments, the object tracking system is implemented that it performs more precisely than existing techniques.
-
Neural network-based feature point descriptors for registration of optical and SAR images
Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry
2018-04-01
Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.
-
Research of image retrieval technology based on color feature
Fu, Yanjun; Jiang, Guangyu; Chen, Fengying
2009-10-01
Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram
-
Improving ELM-Based Service Quality Prediction by Concise Feature Extraction
Directory of Open Access Journals (Sweden)
Yuhai Zhao
2015-01-01
Full Text Available Web services often run on highly dynamic and changing environments, which generate huge volumes of data. Thus, it is impractical to monitor the change of every QoS parameter for the timely trigger precaution due to high computational costs associated with the process. To address the problem, this paper proposes an active service quality prediction method based on extreme learning machine. First, we extract web service trace logs and QoS information from the service log and convert them into feature vectors. Second, by the proposed EC rules, we are enabled to trigger the precaution of QoS as soon as possible with high confidence. An efficient prefix tree based mining algorithm together with some effective pruning rules is developed to mine such rules. Finally, we study how to extract a set of diversified features as the representative of all mined results. The problem is proved to be NP-hard. A greedy algorithm is presented to approximate the optimal solution. Experimental results show that ELM trained by the selected feature subsets can efficiently improve the reliability and the earliness of service quality prediction.
-
A prototype feature system for feature retrieval using relationships
Choi, J.; Usery, E.L.
2009-01-01
Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.
-
Graphical matching rules for cardinality based service feature diagrams
Directory of Open Access Journals (Sweden)
Faiza Kanwal
2017-03-01
Full Text Available To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.
-
Hartshorn, Timothy; Otarodifard, Karimdad; White, Eric A; Hatch, George F Rick
2013-11-01
Little has been written about the use of radiographic landmarks for locating the origin of the superficial medial collateral ligament (sMCL). A standardized radiographic landmark for the sMCL origin using intraoperative fluoroscopic imaging may be of value in aiding the surgeon in accurate femoral tunnel placement in the setting of extensive soft tissue disruption and bony attrition. To determine a reproducible radiographic landmark that will assist in correct femoral tunnel placement in sMCL repair and reconstruction. Descriptive laboratory study. Ten fresh-frozen unmatched human cadaveric knees were dissected, and the origin of the sMCL was exposed. A 2-mm metallic marker was then placed at the center of the femoral origin of the sMCL. True lateral fluoroscopically assisted digital radiographs were obtained of the knee with the posterior and distal femoral condyles overlapping in a standardized fashion. With the use of computer software, reference lines were drawn on the images, creating 4 quadrants. Two independent examiners performed quantitative measurements of the sMCL origin in relation to this axis and to the Blumensaat line. Mean measurements showed the sMCL origin to be closely related to the intersection point of the Blumensaat line and a line drawn distally from the posterior femoral cortex on a true lateral radiograph. The sMCL origin was found at a mean point 1.6 ± 4.3 mm posterior and 4.9 ± 2.1 mm proximal to the intersection of a line paralleling the posterior femoral cortex and a line drawn perpendicular to the posterior femoral cortical line, where it intersects the Blumensaat line. In 5 of 10 specimens, the center of the sMCL origin fell precisely on the Blumensaat line. The remaining specimens had sMCL origins anterior to the Blumensaat line. The femoral origin of the sMCL was found in the proximal and posterior quadrants in 8 of 10 specimens. With a relatively small amount of deviation, the sMCL origin can be consistently identified on a true
-
Registration of cortical surfaces using sulcal landmarks for group analysis of MEG data☆
Joshi, Anand A.; Shattuck, David W.; Thompson, Paul M.; Leahy, Richard M.
2010-01-01
We present a method to register individual cortical surfaces to a surface-based brain atlas or canonical template using labeled sulcal curves as landmark constraints. To map one cortex smoothly onto another, we minimize a thin-plate spline energy defined on the surface by solving the associated partial differential equations (PDEs). By using covariant derivatives in solving these PDEs, we compute the bending energy with respect to the intrinsic geometry of the 3D surface rather than evaluating it in the flattened metric of the 2D parameter space. This covariant approach greatly reduces the confounding effects of the surface parameterization on the resulting registration. PMID:20824115
-
Anatomical landmarks of radical prostatecomy.
Stolzenburg, Jens-Uwe; Schwalenberg, Thilo; Horn, Lars-Christian; Neuhaus, Jochen; Constantinides, Costantinos; Liatsikos, Evangelos N
2007-03-01
In the present study, we review current literature and based on our experience, we present the anatomical landmarks of open and laparoscopic/endoscopic radical prostatectomy. A thorough literature search was performed with the Medline database on the anatomy and the nomenclature of the structures surrounding the prostate gland. The correct handling of puboprostatic ligaments, external urethral sphincter, prostatic fascias and neurovascular bundle is necessary for avoiding malfunction of the urogenital system after radical prostatectomy. When evaluating new prostatectomy techniques, we should always take into account both clinical and final oncological outcomes. The present review adds further knowledge to the existing "postprostatectomy anatomical hazard" debate. It emphasizes upon the role of the puboprostatic ligaments and the course of the external urethral sphincter for urinary continence. When performing an intrafascial nerve sparing prostatectomy most urologists tend to approach as close to the prostatic capsula as possible, even though there is no concurrence regarding the nomenclature of the surrounding fascias and the course of the actual neurovascular bundles. After completion of an intrafascial technique the specimen does not contain any periprostatic tissue and thus the detection of pT3a disease is not feasible. This especially becomes problematic if the tumour reaches the resection margin. Nerve sparing open and laparoscopic radical prostatectomy should aim in maintaining sexual function, recuperating early continence after surgery, without hindering the final oncological outcome to the procedure. Despite the different approaches for radical prostatectomy the key for better results is the understanding of the anatomy of the bladder neck and the urethra.
-
Hariharan, M; Sindhu, R; Vijean, Vikneswaran; Yazid, Haniza; Nadarajaw, Thiyagar; Yaacob, Sazali; Polat, Kemal
2018-03-01
Infant cry signal carries several levels of information about the reason for crying (hunger, pain, sleepiness and discomfort) or the pathological status (asphyxia, deaf, jaundice, premature condition and autism, etc.) of an infant and therefore suited for early diagnosis. In this work, combination of wavelet packet based features and Improved Binary Dragonfly Optimization based feature selection method was proposed to classify the different types of infant cry signals. Cry signals from 2 different databases were utilized. First database contains 507 cry samples of normal (N), 340 cry samples of asphyxia (A), 879 cry samples of deaf (D), 350 cry samples of hungry (H) and 192 cry samples of pain (P). Second database contains 513 cry samples of jaundice (J), 531 samples of premature (Prem) and 45 samples of normal (N). Wavelet packet transform based energy and non-linear entropies (496 features), Linear Predictive Coding (LPC) based cepstral features (56 features), Mel-frequency Cepstral Coefficients (MFCCs) were extracted (16 features). The combined feature set consists of 568 features. To overcome the curse of dimensionality issue, improved binary dragonfly optimization algorithm (IBDFO) was proposed to select the most salient attributes or features. Finally, Extreme Learning Machine (ELM) kernel classifier was used to classify the different types of infant cry signals using all the features and highly informative features as well. Several experiments of two-class and multi-class classification of cry signals were conducted. In binary or two-class experiments, maximum accuracy of 90.18% for H Vs P, 100% for A Vs N, 100% for D Vs N and 97.61% J Vs Prem was achieved using the features selected (only 204 features out of 568) by IBDFO. For the classification of multiple cry signals (multi-class problem), the selected features could differentiate between three classes (N, A & D) with the accuracy of 100% and seven classes with the accuracy of 97.62%. The experimental
-
Feature-based RNN target recognition
Bakircioglu, Hakan; Gelenbe, Erol
1998-09-01
Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.
-
Stress assessment based on EEG univariate features and functional connectivity measures.
Alonso, J F; Romero, S; Ballester, M R; Antonijoan, R M; Mañanas, M A
2015-07-01
The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.
-
DEFF Research Database (Denmark)
Krøjgaard, Peter
. The results obtained using this design reveal that infants are more successful using spatiotemporal object information than when using featural information. However, recent studies using the less cognitively demanding event monitoring design have revealed that even younger infants are capable of object...... in the present series of experiments in which infants' use of spatiotemporal and featural information is compared directly using the less demanding event monitoring design. The results are discussed in relation to existing empirical evidence......., to what extent infants rely on spatiotemporal or featural object information when individuating objects is currently under debate. Hitherto, infants' use of spatiotemporal and featural object information has only been compared directly using the rather cognitively demanding event mapping design...
-
Toward perception-based navigation using EgoSphere
Kawamura, Kazuhiko; Peters, R. Alan; Wilkes, Don M.; Koku, Ahmet B.; Sekman, Ali
2002-02-01
A method for perception-based egocentric navigation of mobile robots is described. Each robot has a local short-term memory structure called the Sensory EgoSphere (SES), which is indexed by azimuth, elevation, and time. Directional sensory processing modules write information on the SES at the location corresponding to the source direction. Each robot has a partial map of its operational area that it has received a priori. The map is populated with landmarks and is not necessarily metrically accurate. Each robot is given a goal location and a route plan. The route plan is a set of via-points that are not used directly. Instead, a robot uses each point to construct a Landmark EgoSphere (LES) a circular projection of the landmarks from the map onto an EgoSphere centered at the via-point. Under normal circumstances, the LES will be mostly unaffected by slight variations in the via-point location. Thus, the route plan is transformed into a set of via-regions each described by an LES. A robot navigates by comparing the next LES in its route plan to the current contents of its SES. It heads toward the indicated landmarks until its SES matches the LES sufficiently to indicate that the robot is near the suggested via-point. The proposed method is particularly useful for enabling the exchange of robust route informa-tion between robots under low data rate communications constraints. An example of such an exchange is given.
-
Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies
Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira
2015-12-01
Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.
-
Directory of Open Access Journals (Sweden)
Julia Mehlhorn
Full Text Available Homing pigeons are known for their excellent homing ability, and their brains seem to be functionally adapted to homing. It is known that pigeons with navigational experience show a larger hippocampus and also a more lateralised brain than pigeons without navigational experience. So we hypothesized that experience may have an influence also on orientation ability. We examined two groups of pigeons (11 with navigational experience and 17 without in a standard operant chamber with a touch screen monitor showing a 2-D schematic of a rectangular environment (as "geometric" information and one uniquely shaped and colored feature in each corner (as "landmark" information. Pigeons were trained first for pecking on one of these features and then we examined their ability to encode geometric and landmark information in four tests by modifying the rectangular environment. All tests were done under binocular and monocular viewing to test hemispheric dominance. The number of pecks was counted for analysis. Results show that generally both groups orientate on the basis of landmarks and the geometry of environment, but landmark information was preferred. Pigeons with navigational experience did not perform better on the tests but showed a better conjunction of the different kinds of information. Significant differences between monocular and binocular viewing were detected particularly in pigeons without navigational experience on two tests with reduced information. Our data suggest that the conjunction of geometric and landmark information might be integrated after processing separately in each hemisphere and that this process is influenced by experience.
-
Mehlhorn, Julia; Rehkaemper, Gerd
2017-01-01
Homing pigeons are known for their excellent homing ability, and their brains seem to be functionally adapted to homing. It is known that pigeons with navigational experience show a larger hippocampus and also a more lateralised brain than pigeons without navigational experience. So we hypothesized that experience may have an influence also on orientation ability. We examined two groups of pigeons (11 with navigational experience and 17 without) in a standard operant chamber with a touch screen monitor showing a 2-D schematic of a rectangular environment (as "geometric" information) and one uniquely shaped and colored feature in each corner (as "landmark" information). Pigeons were trained first for pecking on one of these features and then we examined their ability to encode geometric and landmark information in four tests by modifying the rectangular environment. All tests were done under binocular and monocular viewing to test hemispheric dominance. The number of pecks was counted for analysis. Results show that generally both groups orientate on the basis of landmarks and the geometry of environment, but landmark information was preferred. Pigeons with navigational experience did not perform better on the tests but showed a better conjunction of the different kinds of information. Significant differences between monocular and binocular viewing were detected particularly in pigeons without navigational experience on two tests with reduced information. Our data suggest that the conjunction of geometric and landmark information might be integrated after processing separately in each hemisphere and that this process is influenced by experience.
-
A novel approach for fire recognition using hybrid features and manifold learning-based classifier
Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng
2018-03-01
Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.
-
Liu, Lian; Yang, Xiukun; Zhong, Mingliang; Liu, Yao; Jing, Xiaojun; Yang, Qin
2018-04-01
The discrete fractional Brownian incremental random (DFBIR) field is used to describe the irregular, random, and highly complex shapes of natural objects such as coastlines and biological tissues, for which traditional Euclidean geometry cannot be used. In this paper, an anisotropic variable window (AVW) directional operator based on the DFBIR field model is proposed for extracting spatial characteristics of Fourier transform infrared spectroscopy (FTIR) microscopic imaging. Probabilistic principal component analysis first extracts spectral features, and then the spatial features of the proposed AVW directional operator are combined with the former to construct a spatial-spectral structure, which increases feature-related information and helps a support vector machine classifier to obtain more efficient distribution-related information. Compared to Haralick’s grey-level co-occurrence matrix, Gabor filters, and local binary patterns (e.g. uniform LBPs, rotation-invariant LBPs, uniform rotation-invariant LBPs), experiments on three FTIR spectroscopy microscopic imaging datasets show that the proposed AVW directional operator is more advantageous in terms of classification accuracy, particularly for low-dimensional spaces of spatial characteristics.
-
Feature-Based Nonlocal Polarimetric SAR Filtering
Directory of Open Access Journals (Sweden)
Xiaoli Xing
2017-10-01
Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.
-
TOWARD SEMANTIC WEB INFRASTRUCTURE FOR SPATIAL FEATURES' INFORMATION
Directory of Open Access Journals (Sweden)
R. Arabsheibani
2015-12-01
Full Text Available The Web and its capabilities can be employed as a tool for data and information integration if comprehensive datasets and appropriate technologies and standards enable the web with interpretation and easy alignment of data and information. Semantic Web along with the spatial functionalities enable the web to deal with the huge amount of data and information. The present study investigate the advantages and limitations of the Spatial Semantic Web and compare its capabilities with relational models in order to build a spatial data infrastructure. An architecture is proposed and a set of criteria is defined for the efficiency evaluation. The result demonstrate that when using the data with special characteristics such as schema dynamicity, sparse data or available relations between the features, the spatial semantic web and graph databases with spatial operations are preferable.
-
On-board landmark navigation and attitude reference parallel processor system
Gilbert, L. E.; Mahajan, D. T.
1978-01-01
An approach to autonomous navigation and attitude reference for earth observing spacecraft is described along with the landmark identification technique based on a sequential similarity detection algorithm (SSDA). Laboratory experiments undertaken to determine if better than one pixel accuracy in registration can be achieved consistent with onboard processor timing and capacity constraints are included. The SSDA is implemented using a multi-microprocessor system including synchronization logic and chip library. The data is processed in parallel stages, effectively reducing the time to match the small known image within a larger image as seen by the onboard image system. Shared memory is incorporated in the system to help communicate intermediate results among microprocessors. The functions include finding mean values and summation of absolute differences over the image search area. The hardware is a low power, compact unit suitable to onboard application with the flexibility to provide for different parameters depending upon the environment.
-
Smith, Nicolina M; Segars, Larry; Kauffman, Travis; Olinger, Anthony B
2017-12-01
Atrial fibrillation (AF) is an arrhythmia which affects as many as 2.7 million Americans. AF should be treated, because it can lead to a four-to-fivefold increased risk of experiencing a stroke. The American College of Cardiology/American Heart Association guidelines for the treatment of drug refractory and symptomatic paroxysmal AF denote catheter ablation as the standard of care. The newest ablation treatment, cryoballoon, uses a cold balloon tip. The biggest risk factor associated with the cryoballoon ablation is phrenic nerve injury (PNI). The purpose of this study is to measure relevant distances from specific landmarks to the right phrenic nerve (RPN) to create a safe zone for physicians. Using 30 cadaveric specimens, we measured laterally from the right superior pulmonary vein orifice (RSPV) to the RPN at the level of the sixth thoracic vertebra and laterally from the lateral border of the sixth thoracic vertebral body (T6) to the RPN. The depth and width of the left atrium (LA) were also measured to establish a cross-sectional area of the LA. The cross-sectional area of the LA was then correlated with the averaged measurements to see if the area of the LA could be a predictor of the location of the RPN. The average distance from the RPN-RSPV was 9.6 mm (range 4.3-18.8 mm). The average RPN-T6 distance was 30.6 mm (range 13.7-49.9 mm). There was a non-significant trend that suggests as the size of the LA increases, the measured distances also increased. Using the lateral border of the sixth thoracic vertebra as a landmark, which can be viewed under fluoroscopy during the procedure, physicians can triangulate the distance to the RSPV and determine the approximate position of the RPN. Furthermore, physicians can perform a preoperative echocardiogram to determine the size of the LA to assist in determining the position of the RPN with the hopes of avoiding injury to the RPN.
-
Global Polity in Adult Education and UNESCO: Landmarking, Brokering and Framing Policy
Milana, Marcella
2016-01-01
Aknowledging the complexity of local-global interconnections, the author argues for the adoption of a global polity perspective in adult education, here applied to study mobilisation processes that occur through UNESCO. The findings point to three processes that cross geopolitical borders and professional interests: "landmarking," by…
-
Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses
Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn
2016-01-01
Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however
-
Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.
Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn
2016-01-26
Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than
-
Contact-free palm-vein recognition based on local invariant features.
Directory of Open Access Journals (Sweden)
Wenxiong Kang
Full Text Available Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs, respectively, which demonstrate the effectiveness of the proposed approach.
-
Contact-free palm-vein recognition based on local invariant features.
Kang, Wenxiong; Liu, Yang; Wu, Qiuxia; Yue, Xishun
2014-01-01
Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach.
-
Ship Detection Based on Multiple Features in Random Forest Model for Hyperspectral Images
Li, N.; Ding, L.; Zhao, H.; Shi, J.; Wang, D.; Gong, X.
2018-04-01
A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in the range of near infrared or short-wave infrared spectrum, is used to segment land and sea on Otsu threshold segmentation method. Secondly, multiple features that include spectral and texture features are extracted from hyperspectral images. Principal components analysis (PCA) is used to extract spectral features, the Grey Level Co-occurrence Matrix (GLCM) is used to extract texture features. Finally, Random Forest (RF) model is introduced to detect ships based on the extracted features. To illustrate the effectiveness of the method, we carry out experiments over the EO-1 data by comparing single feature and different multiple features. Compared with the traditional single feature method and Support Vector Machine (SVM) model, the proposed method can stably achieve the target detection of ships under complex background and can effectively improve the detection accuracy of ships.
-
Hwang, Jae Joon; Kim, Kee-Deog; Park, Hyok; Park, Chang Seo; Jeong, Ho-Gul
2014-01-01
Superimposition has been used as a method to evaluate the changes of orthodontic or orthopedic treatment in the dental field. With the introduction of cone beam CT (CBCT), evaluating 3 dimensional changes after treatment became possible by superimposition. 4 point plane orientation is one of the simplest ways to achieve superimposition of 3 dimensional images. To find factors influencing superimposition error of cephalometric landmarks by 4 point plane orientation method and to evaluate the reproducibility of cephalometric landmarks for analyzing superimposition error, 20 patients were analyzed who had normal skeletal and occlusal relationship and took CBCT for diagnosis of temporomandibular disorder. The nasion, sella turcica, basion and midpoint between the left and the right most posterior point of the lesser wing of sphenoidal bone were used to define a three-dimensional (3D) anatomical reference co-ordinate system. Another 15 reference cephalometric points were also determined three times in the same image. Reorientation error of each landmark could be explained substantially (23%) by linear regression model, which consists of 3 factors describing position of each landmark towards reference axes and locating error. 4 point plane orientation system may produce an amount of reorientation error that may vary according to the perpendicular distance between the landmark and the x-axis; the reorientation error also increases as the locating error and shift of reference axes viewed from each landmark increases. Therefore, in order to reduce the reorientation error, accuracy of all landmarks including the reference points is important. Construction of the regression model using reference points of greater precision is required for the clinical application of this model.
-
Wang, Yongzhi; Ma, Yuqing; Zhu, A.-xing; Zhao, Hui; Liao, Lixia
2018-05-01
Facade features represent segmentations of building surfaces and can serve as a building framework. Extracting facade features from three-dimensional (3D) point cloud data (3D PCD) is an efficient method for 3D building modeling. By combining the advantages of 3D PCD and two-dimensional optical images, this study describes the creation of a highly accurate building facade feature extraction method from 3D PCD with a focus on structural information. The new extraction method involves three major steps: image feature extraction, exploration of the mapping method between the image features and 3D PCD, and optimization of the initial 3D PCD facade features considering structural information. Results show that the new method can extract the 3D PCD facade features of buildings more accurately and continuously. The new method is validated using a case study. In addition, the effectiveness of the new method is demonstrated by comparing it with the range image-extraction method and the optical image-extraction method in the absence of structural information. The 3D PCD facade features extracted by the new method can be applied in many fields, such as 3D building modeling and building information modeling.
-
Cook, David A; Hamstra, Stanley J; Brydges, Ryan; Zendejas, Benjamin; Szostek, Jason H; Wang, Amy T; Erwin, Patricia J; Hatala, Rose
2013-01-01
Although technology-enhanced simulation is increasingly used in health professions education, features of effective simulation-based instructional design remain uncertain. Evaluate the effectiveness of instructional design features through a systematic review of studies comparing different simulation-based interventions. We systematically searched MEDLINE, EMBASE, CINAHL, ERIC, PsycINFO, Scopus, key journals, and previous review bibliographies through May 2011. We included original research studies that compared one simulation intervention with another and involved health professions learners. Working in duplicate, we evaluated study quality and abstracted information on learners, outcomes, and instructional design features. We pooled results using random effects meta-analysis. From a pool of 10,903 articles we identified 289 eligible studies enrolling 18,971 trainees, including 208 randomized trials. Inconsistency was usually large (I2 > 50%). For skills outcomes, pooled effect sizes (positive numbers favoring the instructional design feature) were 0.68 for range of difficulty (20 studies; p simulation-based education.
-
Kernel-based discriminant feature extraction using a representative dataset
Li, Honglin; Sancho Gomez, Jose-Luis; Ahalt, Stanley C.
2002-07-01
Discriminant Feature Extraction (DFE) is widely recognized as an important pre-processing step in classification applications. Most DFE algorithms are linear and thus can only explore the linear discriminant information among the different classes. Recently, there has been several promising attempts to develop nonlinear DFE algorithms, among which is Kernel-based Feature Extraction (KFE). The efficacy of KFE has been experimentally verified by both synthetic data and real problems. However, KFE has some known limitations. First, KFE does not work well for strongly overlapped data. Second, KFE employs all of the training set samples during the feature extraction phase, which can result in significant computation when applied to very large datasets. Finally, KFE can result in overfitting. In this paper, we propose a substantial improvement to KFE that overcomes the above limitations by using a representative dataset, which consists of critical points that are generated from data-editing techniques and centroid points that are determined by using the Frequency Sensitive Competitive Learning (FSCL) algorithm. Experiments show that this new KFE algorithm performs well on significantly overlapped datasets, and it also reduces computational complexity. Further, by controlling the number of centroids, the overfitting problem can be effectively alleviated.
-
Text feature extraction based on deep learning: a review.
Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan
2017-01-01
Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.
-
Directory of Open Access Journals (Sweden)
Md. Rabiul Islam
2014-01-01
Full Text Available The aim of the paper is to propose a feature fusion based Audio-Visual Speaker Identification (AVSI system with varied conditions of illumination environments. Among the different fusion strategies, feature level fusion has been used for the proposed AVSI system where Hidden Markov Model (HMM is used for learning and classification. Since the feature set contains richer information about the raw biometric data than any other levels, integration at feature level is expected to provide better authentication results. In this paper, both Mel Frequency Cepstral Coefficients (MFCCs and Linear Prediction Cepstral Coefficients (LPCCs are combined to get the audio feature vectors and Active Shape Model (ASM based appearance and shape facial features are concatenated to take the visual feature vectors. These combined audio and visual features are used for the feature-fusion. To reduce the dimension of the audio and visual feature vectors, Principal Component Analysis (PCA method is used. The VALID audio-visual database is used to measure the performance of the proposed system where four different illumination levels of lighting conditions are considered. Experimental results focus on the significance of the proposed audio-visual speaker identification system with various combinations of audio and visual features.
-
Fashion Evaluation Method for Clothing Recommendation Based on Weak Appearance Feature
Directory of Open Access Journals (Sweden)
Yan Zhang
2017-01-01
Full Text Available With the rapid rising of living standard, people gradually developed higher shopping enthusiasm and increasing demand for garment. Nowadays, an increasing number of people pursue fashion. However, facing too many types of garment, consumers need to try them on repeatedly, which is somewhat time- and energy-consuming. Besides, it is difficult for merchants to master the real-time demand of consumers. Herein, there is not enough cohesiveness between consumer information and merchants. Thus, a novel fashion evaluation method on the basis of the appearance weak feature is proposed in this paper. First of all, image database is established and three aspects of appearance weak feature are put forward to characterize the fashion level. Furthermore, the appearance weak features are extracted according to the characters’ facial feature localization method. Last but not least, consumers’ fashion level can be classified through support vector product, and the classification is verified with the hierarchical analysis method. The experimental results show that consumers’ fashion level can be accurately described based on the indexes of appearance weak feature and the approach has higher application value for the clothing recommendation system.
-
Ultrasound guidance versus anatomical landmarks for internal jugular vein catheterization.
Brass, Patrick; Hellmich, Martin; Kolodziej, Laurentius; Schick, Guido; Smith, Andrew F
2015-01-09
definition for this outcome; MD 62.04 seconds, 95% CI -13.47 to 137.55; P value 0.11) when Doppler ultrasound was used. It was not possible to perform analyses for the other outcomes because they were reported in only one trial. Based on available data, we conclude that two-dimensional ultrasound offers gains in safety and quality when compared with an anatomical landmark technique. Because of missing data, we did not compare effects with experienced versus inexperienced operators for all outcomes (arterial puncture, haematoma formation, other complications, success with attempt number one), and so the relative utility of ultrasound in these groups remains unclear and no data are available on use of this technique in patients at high risk of complications. The results for Doppler ultrasound techniques versus anatomical landmark techniques are also uncertain.
-
Vision-based mapping with cooperative robots
Little, James J.; Jennings, Cullen; Murray, Don
1998-10-01
Two stereo-vision-based mobile robots navigate and autonomously explore their environment safely while building occupancy grid maps of the environment. The robots maintain position estimates within a global coordinate frame using landmark recognition. This allows them to build a common map by sharing position information and stereo data. Stereo vision processing and map updates are done at 3 Hz and the robots move at speeds of 200 cm/s. Cooperative mapping is achieved through autonomous exploration of unstructured and dynamic environments. The map is constructed conservatively, so as to be useful for collision-free path planning. Each robot maintains a separate copy of a shared map, and then posts updates to the common map when it returns to observe a landmark at home base. Issues include synchronization, mutual localization, navigation, exploration, registration of maps, merging repeated views (fusion), centralized vs decentralized maps.
-
Hoang, Thu-Huong; Aliane, Verena; Manahan-Vaughan, Denise
2018-05-01
The specific roles of hippocampal subfields in spatial information processing and encoding are, as yet, unclear. The parallel map theory postulates that whereas the CA1 processes discrete environmental features (positional cues used to generate a "sketch map"), the dentate gyrus (DG) processes large navigation-relevant landmarks (directional cues used to generate a "bearing map"). Additionally, the two-streams hypothesis suggests that hippocampal subfields engage in differentiated processing of information from the "where" and the "what" streams. We investigated these hypotheses by analyzing the effect of exploration of discrete "positional" features and large "directional" spatial landmarks on hippocampal neuronal activity in rats. As an indicator of neuronal activity we measured the mRNA induction of the immediate early genes (IEGs), Arc and Homer1a. We observed an increase of this IEG mRNA in CA1 neurons of the distal neuronal compartment and in proximal CA3, after novel spatial exploration of discrete positional cues, whereas novel exploration of directional cues led to increases in IEG mRNA in the lower blade of the DG and in proximal CA3. Strikingly, the CA1 did not respond to directional cues and the DG did not respond to positional cues. Our data provide evidence for both the parallel map theory and the two-streams hypothesis and suggest a precise compartmentalization of the encoding and processing of "what" and "where" information occurs within the hippocampal subfields. © 2018 The Authors. Hippocampus Published by Wiley Periodicals, Inc.
-
Interactive Information Service Technology of Tea Industry Based on Demand-Driven
Shi , Xiaohui; Chen , Tian’en
2013-01-01
International audience; Information service technology is a bridge between user and information resource, also is the critical factor to weight the quality of information service. Focusing on the information service features of tea industry, the demand-driven and interaction of information service were emphasized in this paper. User and market as the major criterion for testing the quality of information service, the interactive information service mode based on the demand-driven was proposed...
-
International Nuclear Information System (INIS)
Shin, Jeong Won; Heo, Min Suk; Lee, Sam Sun; Choi, Hyun Bae; Choi, Soon Chul; Choi, Hang Moon
2002-01-01
Computed radiography (CR) has been used in cephalometric radiography and many studies have been carried out to improve image quality using various digital enhancement and filtering techniques. During CR image acquisition, the frequency rank and type affect to the image quality. The aim of this study was to compare the diagnostic quality of conventional cephalometric radiographs to those of computed radiography. The diagnostic quality of conventional cephalometric radiographs (M0) and their digital image counterparts were compared, and at the same time, six modalities (M1-M6) of spatial frequency-processed digital images were compared by evaluating the reproducibility of 23 cephalometric landmark locations. Reproducibility was defined as an observer's deviation (in mm) from the mean between all observers. In comparison with the conventional cephalometric radiograph (M0), M1 showed statistically significant differences in 8 locations, M2 in 9, M3 12, M4 in 7, M5 in 12, and M6 showed significant differences in 14 of 23 landmark locations (p<0.05). The number of reproducible landmarks that each modality possesses were 7 in M6, 6 in M5, 5 in M3, 4 in M4, 3 in M2, 2 in M1, and 1 location in M0. The image modality that observers selected as having the best image quality was M5.
-
Dependency Parsing with Transformed Feature
Directory of Open Access Journals (Sweden)
Fuxiang Wu
2017-01-01
Full Text Available Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the un-indexed strings and alleviate the feature sparse problem. The model transforms the extracted features to transformed features via applying a feature weight matrix, which consists of similarities between the feature strings. Since the matrix is usually rank-deficient because of similar feature strings, it would influence the strength of constraints. However, it is proven that the duplicate transformed features do not degrade the optimization algorithm: the margin infused relaxed algorithm. Moreover, this problem can be alleviated by reducing the number of the nearest transformed features of a feature. In addition, to further improve the parsing accuracy, a fusion parser is introduced to integrate transformed and original features. Our experiments verify that both transform-based and fusion parser improve the parsing accuracy compared to the corresponding feature-based parser.
-
A kernel-based multi-feature image representation for histopathology image classification
International Nuclear Information System (INIS)
Moreno J; Caicedo J Gonzalez F
2010-01-01
This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.
-
A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION
Directory of Open Access Journals (Sweden)
J Carlos Moreno
2010-09-01
Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.
-
Park, Hyunjin; Park, Jun-Sung; Seong, Joon-Kyung; Na, Duk L; Lee, Jong-Min
2012-04-30
Analysis of cortical patterns requires accurate cortical surface registration. Many researchers map the cortical surface onto a unit sphere and perform registration of two images defined on the unit sphere. Here we have developed a novel registration framework for the cortical surface based on spherical thin-plate splines. Small-scale composition of spherical thin-plate splines was used as the geometric interpolant to avoid folding in the geometric transform. Using an automatic algorithm based on anisotropic skeletons, we extracted seven sulcal lines, which we then incorporated as landmark information. Mean curvature was chosen as an additional feature for matching between spherical maps. We employed a two-term cost function to encourage matching of both sulcal lines and the mean curvature between the spherical maps. Application of our registration framework to fifty pairwise registrations of T1-weighted MRI scans resulted in improved registration accuracy, which was computed from sulcal lines. Our registration approach was tested as an additional procedure to improve an existing surface registration algorithm. Our registration framework maintained an accurate registration over the sulcal lines while significantly increasing the cross-correlation of mean curvature between the spherical maps being registered. Copyright © 2012 Elsevier B.V. All rights reserved.
-
Method of mobile robot indoor navigation by artificial landmarks with use of computer vision
Glibin, E. S.; Shevtsov, A. A.; Enik, O. A.
2018-05-01
The article describes an algorithm of the mobile robot indoor navigation based on the use of visual odometry. The results of the experiment identifying calculation errors in the distance traveled on a slip are presented. It is shown that the use of computer vision allows one to correct erroneous coordinates of the robot with the help of artificial landmarks. The control system utilizing the proposed method has been realized on the basis of Arduino Mego 2560 controller and a single-board computer Raspberry Pi 3. The results of the experiment on the mobile robot navigation with the use of this control system are presented.
-
Dolloff, John; Hottel, Bryant; Edwards, David; Theiss, Henry; Braun, Aaron
2017-05-01
This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.
-
Joint spatial-depth feature pooling for RGB-D object classification
DEFF Research Database (Denmark)
Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping
2015-01-01
RGB-D camera can provide effective support with additional depth cue for many RGB-D perception tasks beyond traditional RGB information. However, current feature representations based on RGB-D camera utilize depth information only to extract local features, without considering it for the improvem......RGB-D camera can provide effective support with additional depth cue for many RGB-D perception tasks beyond traditional RGB information. However, current feature representations based on RGB-D camera utilize depth information only to extract local features, without considering...
-
Taylor, Kirsten I; Devereux, Barry J; Acres, Kadia; Randall, Billi; Tyler, Lorraine K
2012-03-01
Conceptual representations are at the heart of our mental lives, involved in every aspect of cognitive functioning. Despite their centrality, a long-standing debate persists as to how the meanings of concepts are represented and processed. Many accounts agree that the meanings of concrete concepts are represented by their individual features, but disagree about the importance of different feature-based variables: some views stress the importance of the information carried by distinctive features in conceptual processing, others the features which are shared over many concepts, and still others the extent to which features co-occur. We suggest that previously disparate theoretical positions and experimental findings can be unified by an account which claims that task demands determine how concepts are processed in addition to the effects of feature distinctiveness and co-occurrence. We tested these predictions in a basic-level naming task which relies on distinctive feature information (Experiment 1) and a domain decision task which relies on shared feature information (Experiment 2). Both used large-scale regression designs with the same visual objects, and mixed-effects models incorporating participant, session, stimulus-related and feature statistic variables to model the performance. We found that concepts with relatively more distinctive and more highly correlated distinctive relative to shared features facilitated basic-level naming latencies, while concepts with relatively more shared and more highly correlated shared relative to distinctive features speeded domain decisions. These findings demonstrate that the feature statistics of distinctiveness (shared vs. distinctive) and correlational strength, as well as the task demands, determine how concept meaning is processed in the conceptual system. Copyright © 2011 Elsevier B.V. All rights reserved.
-
Dekavalla, Maria; Argialas, Demetre
2017-07-01
The analysis of undersea topography and geomorphological features provides necessary information to related disciplines and many applications. The development of an automated knowledge-based classification approach of undersea topography and geomorphological features is challenging due to their multi-scale nature. The aim of the study is to develop and evaluate an automated knowledge-based OBIA approach to: i) decompose the global undersea topography to multi-scale regions of distinct morphometric properties, and ii) assign the derived regions to characteristic geomorphological features. First, the global undersea topography was decomposed through the SRTM30_PLUS bathymetry data to the so-called morphometric objects of discrete morphometric properties and spatial scales defined by data-driven methods (local variance graphs and nested means) and multi-scale analysis. The derived morphometric objects were combined with additional relative topographic position information computed with a self-adaptive pattern recognition method (geomorphons), and auxiliary data and were assigned to characteristic undersea geomorphological feature classes through a knowledge base, developed from standard definitions. The decomposition of the SRTM30_PLUS data to morphometric objects was considered successful for the requirements of maximizing intra-object and inter-object heterogeneity, based on the near zero values of the Moran's I and the low values of the weighted variance index. The knowledge-based classification approach was tested for its transferability in six case studies of various tectonic settings and achieved the efficient extraction of 11 undersea geomorphological feature classes. The classification results for the six case studies were compared with the digital global seafloor geomorphic features map (GSFM). The 11 undersea feature classes and their producer's accuracies in respect to the GSFM relevant areas were Basin (95%), Continental Shelf (94.9%), Trough (88
-
An approach to robot SLAM based on incremental appearance learning with omnidirectional vision
Wu, Hua; Qin, Shi-Yin
2011-03-01
Localisation and mapping with an omnidirectional camera becomes more difficult as the landmark appearances change dramatically in the omnidirectional image. With conventional techniques, it is difficult to match the features of the landmark with the template. We present a novel robot simultaneous localisation and mapping (SLAM) algorithm with an omnidirectional camera, which uses incremental landmark appearance learning to provide posterior probability distribution for estimating the robot pose under a particle filtering framework. The major contribution of our work is to represent the posterior estimation of the robot pose by incremental probabilistic principal component analysis, which can be naturally incorporated into the particle filtering algorithm for robot SLAM. Moreover, the innovative method of this article allows the adoption of the severe distorted landmark appearances viewed with omnidirectional camera for robot SLAM. The experimental results demonstrate that the localisation error is less than 1 cm in an indoor environment using five landmarks, and the location of the landmark appearances can be estimated within 5 pixels deviation from the ground truth in the omnidirectional image at a fairly fast speed.
-
vSLAM: vision-based SLAM for autonomous vehicle navigation
Goncalves, Luis; Karlsson, Niklas; Ostrowski, Jim; Di Bernardo, Enrico; Pirjanian, Paolo
2004-09-01
Among the numerous challenges of building autonomous/unmanned vehicles is that of reliable and autonomous localization in an unknown environment. In this paper we present a system that can efficiently and autonomously solve the robotics 'SLAM' problem, where a robot placed in an unknown environment, simultaneously must localize itself and make a map of the environment. The system is vision-based, and makes use of Evolution Robotic's powerful object recognition technology. As the robot explores the environment, it is continuously performing four tasks, using information from acquired images and the drive system odometry. The robot: (1) recognizes previously created 3-D visual landmarks; (2) builds new 3-D visual landmarks; (3) updates the current estimate of its location, using the map; (4) updates the landmark map. In indoor environments, the system can build a map of a 5m by 5m area in approximately 20 minutes, and can localize itself with an accuracy of approximately 15 cm in position and 3 degrees in orientation relative to the global reference frame of the landmark map. The same system can be adapted for outdoor, vehicular use.
-
Entropy Based Feature Selection for Fuzzy Set-Valued Information Systems
Ahmed, Waseem; Sufyan Beg, M. M.; Ahmad, Tanvir
2018-06-01
In Set-valued Information Systems (SIS), several objects contain more than one value for some attributes. Tolerance relation used for handling SIS sometimes leads to loss of certain information. To surmount this problem, fuzzy rough model was introduced. However, in some cases, SIS may contain some real or continuous set-values. Therefore, the existing fuzzy rough model for handling Information system with fuzzy set-values needs some changes. In this paper, Fuzzy Set-valued Information System (FSIS) is proposed and fuzzy similarity relation for FSIS is defined. Yager's relative conditional entropy was studied to find the significance measure of a candidate attribute of FSIS. Later, using these significance values, three greedy forward algorithms are discussed for finding the reduct and relative reduct for the proposed FSIS. An experiment was conducted on a sample population of the real dataset and a comparison of classification accuracies of the proposed FSIS with the existing SIS and single-valued Fuzzy Information Systems was made, which demonstrated the effectiveness of proposed FSIS.
-
NetProt: Complex-based Feature Selection.
Goh, Wilson Wen Bin; Wong, Limsoon
2017-08-04
Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .
-
Directory of Open Access Journals (Sweden)
Abdallah S.R. Mohamed
2017-12-01
Full Text Available Purpose: Uncertainties related to geometric distortion are a major obstacle for effectively utilizing MRI in radiation oncology. We aim to quantify the geometric distortion in patient images by comparing their in-treatment position MRIs with the corresponding planning CTs, using CT as the non-distorted gold standard. Methods: Twenty-one head and neck cancer patients were imaged with MRI as part of a prospective Institutional Review Board approved study. MR images were acquired with a T2 SE sequence (0.5 Ã 0.5 Ã 2.5 mm voxel size in the same immobilization position as in the CTs. MRI to CT rigid registration was then done and geometric distortion comparison was assessed by measuring the corresponding anatomical landmarks on both the MRI and the CT images. Several landmark measurements were obtained including; skin to skin (STS, bone to bone, and soft tissue to soft tissue at specific levels in horizontal and vertical planes of both scans. Inter-observer variability was assessed and interclass correlation (ICC was calculated. Results: A total of 430 landmark measurements were obtained. The median distortion for all landmarks in all scans was 1.06 mm (IQR 0.6â1.98. For each patient 48% of the measurements were done in the right-left direction and 52% were done in the anteroposterior direction. The measured geometric distortion was not statistically different in the right-left direction compared to the anteroposterior direction (1.5 ± 1.6 vs. 1.6 ± 1.7 mm, respectively, p = 0.4. The magnitude of distortion was higher in the STS peripheral landmarks compared to the more central landmarks (2.0 ± 1.9 vs. 1.2 ± 1.3 mm, p < 0.0001. The mean distortion measured by observer one was not significantly different compared to observer 2, 3, and 4 (1.05, 1.23, 1.06 and 1.05 mm, respectively, p = 0.4 with ICC = 0.84. Conclusion: MRI geometric distortions were
-
Automatic building extraction from LiDAR data fusion of point and grid-based features
Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang
2017-08-01
This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.
-
Maes, J.H.R.; Fontanari, L.; Regolin, L.
2009-01-01
Rats were used in a spatial reorientation task to assess their ability to use geometric and non-geometric, featural, information. Experimental conditions differed in the size of the arena (small, medium, or large) and whether the food-baited corner was near or far from a visual feature. The main
-
Lin, Hsiu-Hsia; Chuang, Ya-Fang; Weng, Jing-Ling; Lo, Lun-Jou
2015-01-01
Three-dimensional computed tomographic imaging has become popular in clinical evaluation, treatment planning, surgical simulation, and outcome assessment for maxillofacial intervention. The purposes of this study were to investigate whether there is any correlation among landmark-based horizontal reference planes and to validate the reproducibility and reliability of landmark identification. Preoperative and postoperative cone-beam computed tomographic images of patients who had undergone orthognathic surgery were collected. Landmark-oriented reference planes including the Frankfort horizontal plane (FHP) and the lateral semicircular canal plane (LSP) were established. Four FHPs were defined by selecting 3 points from the orbitale, porion, or midpoint of paired points. The LSP passed through both the lateral semicircular canal points and nasion. The distances between the maxillary or mandibular teeth and the reference planes were measured, and the differences between the 2 sides were calculated and compared. The precision in locating the landmarks was evaluated by performing repeated tests, and the intraobserver reproducibility and interobserver reliability were assessed. A total of 30 patients with facial deformity and malocclusion--10 patients with facial symmetry, 10 patients with facial asymmetry, and 10 patients with cleft lip and palate--were recruited. Comparing the differences among the 5 reference planes showed no statistically significant difference among all patient groups. Regarding intraobserver reproducibility, the mean differences in the 3 coordinates varied from 0 to 0.35 mm, with correlation coefficients between 0.96 and 1.0, showing high correlation between repeated tests. Regarding interobserver reliability, the mean differences among the 3 coordinates varied from 0 to 0.47 mm, with correlation coefficients between 0.88 and 1.0, exhibiting high correlation between the different examiners. The 5 horizontal reference planes were reliable and
-
Introduction to information science
Bawden, David
2012-01-01
This landmark textbook takes a whole subject approach to Information Science as a discipline. Introduced by leading international scholars and offering a global perspective on the discipline, this is designed to be the standard text for students worldwide. The authors' expert narrative guides you through each of the essential building blocks of information science offering a concise introduction and expertly chosen further reading and resources.Critical topics covered include:foundations: concepts, theories and historical perspectivesorganising and retrieving Information information behaviour,
-
A multicore based parallel image registration method.
Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L; Foran, David J
2009-01-01
Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform.
-
Modeling the Time Course of Feature Perception and Feature Information Retrieval
Kent, Christopher; Lamberts, Koen
2006-01-01
Three experiments investigated whether retrieval of information about different dimensions of a visual object varies as a function of the perceptual properties of those dimensions. The experiments involved two perception-based matching tasks and two retrieval-based matching tasks. A signal-to-respond methodology was used in all tasks. A stochastic…
-
Directory of Open Access Journals (Sweden)
Bo Peng
2017-05-01
Full Text Available Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR images using multilevel-features-based classification method.Method: The multilevel region of interest (ROI features consist of two types of features: (i ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs with appropriate weighting factor.Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions.Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.
-
Single-labelled music genre classification using content-based features
CSIR Research Space (South Africa)
Ajoodha, R
2015-11-01
Full Text Available In this paper we use content-based features to perform automatic classification of music pieces into genres. We categorise these features into four groups: features extracted from the Fourier transform’s magnitude spectrum, features designed...
-
Feature representation of RGB-D images using joint spatial-depth feature pooling
DEFF Research Database (Denmark)
Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping
2016-01-01
Recent development in depth imaging technology makes acquisition of depth information easier. With the additional depth cue, RGB-D cameras can provide effective support for many RGB-D perception tasks beyond traditional RGB information. However, current feature representation based on RGB-D image...
-
Directory of Open Access Journals (Sweden)
Peng Shao
2014-08-01
Full Text Available The principle of multiresolution segmentation was represented in detail in this study, and the canny algorithm was applied for edge-detection of a remotely sensed image based on this principle. The target image was divided into regions based on object-oriented multiresolution segmentation and edge-detection. Furthermore, object hierarchy was created, and a series of features (water bodies, vegetation, roads, residential areas, bare land and other information were extracted by the spectral and geometrical features. The results indicate that the edge-detection has a positive effect on multiresolution segmentation, and overall accuracy of information extraction reaches to 94.6% by the confusion matrix.
-
A Knowledge Base for Automatic Feature Recognition from Point Clouds in an Urban Scene
Directory of Open Access Journals (Sweden)
Xu-Feng Xing
2018-01-01
Full Text Available LiDAR technology can provide very detailed and highly accurate geospatial information on an urban scene for the creation of Virtual Geographic Environments (VGEs for different applications. However, automatic 3D modeling and feature recognition from LiDAR point clouds are very complex tasks. This becomes even more complex when the data is incomplete (occlusion problem or uncertain. In this paper, we propose to build a knowledge base comprising of ontology and semantic rules aiming at automatic feature recognition from point clouds in support of 3D modeling. First, several modules for ontology are defined from different perspectives to describe an urban scene. For instance, the spatial relations module allows the formalized representation of possible topological relations extracted from point clouds. Then, a knowledge base is proposed that contains different concepts, their properties and their relations, together with constraints and semantic rules. Then, instances and their specific relations form an urban scene and are added to the knowledge base as facts. Based on the knowledge and semantic rules, a reasoning process is carried out to extract semantic features of the objects and their components in the urban scene. Finally, several experiments are presented to show the validity of our approach to recognize different semantic features of buildings from LiDAR point clouds.
-
Analyzing locomotion synthesis with feature-based motion graphs.
Mahmudi, Mentar; Kallmann, Marcelo
2013-05-01
We propose feature-based motion graphs for realistic locomotion synthesis among obstacles. Among several advantages, feature-based motion graphs achieve improved results in search queries, eliminate the need of postprocessing for foot skating removal, and reduce the computational requirements in comparison to traditional motion graphs. Our contributions are threefold. First, we show that choosing transitions based on relevant features significantly reduces graph construction time and leads to improved search performances. Second, we employ a fast channel search method that confines the motion graph search to a free channel with guaranteed clearance among obstacles, achieving faster and improved results that avoid expensive collision checking. Lastly, we present a motion deformation model based on Inverse Kinematics applied over the transitions of a solution branch. Each transition is assigned a continuous deformation range that does not exceed the original transition cost threshold specified by the user for the graph construction. The obtained deformation improves the reachability of the feature-based motion graph and in turn also reduces the time spent during search. The results obtained by the proposed methods are evaluated and quantified, and they demonstrate significant improvements in comparison to traditional motion graph techniques.
-
Subject-based feature extraction by using fisher WPD-CSP in brain-computer interfaces.
Yang, Banghua; Li, Huarong; Wang, Qian; Zhang, Yunyuan
2016-06-01
Feature extraction of electroencephalogram (EEG) plays a vital role in brain-computer interfaces (BCIs). In recent years, common spatial pattern (CSP) has been proven to be an effective feature extraction method. However, the traditional CSP has disadvantages of requiring a lot of input channels and the lack of frequency information. In order to remedy the defects of CSP, wavelet packet decomposition (WPD) and CSP are combined to extract effective features. But WPD-CSP method considers less about extracting specific features that are fitted for the specific subject. So a subject-based feature extraction method using fisher WPD-CSP is proposed in this paper. The idea of proposed method is to adapt fisher WPD-CSP to each subject separately. It mainly includes the following six steps: (1) original EEG signals from all channels are decomposed into a series of sub-bands using WPD; (2) average power values of obtained sub-bands are computed; (3) the specified sub-bands with larger values of fisher distance according to average power are selected for that particular subject; (4) each selected sub-band is reconstructed to be regarded as a new EEG channel; (5) all new EEG channels are used as input of the CSP and a six-dimensional feature vector is obtained by the CSP. The subject-based feature extraction model is so formed; (6) the probabilistic neural network (PNN) is used as the classifier and the classification accuracy is obtained. Data from six subjects are processed by the subject-based fisher WPD-CSP, the non-subject-based fisher WPD-CSP and WPD-CSP, respectively. Compared with non-subject-based fisher WPD-CSP and WPD-CSP, the results show that the proposed method yields better performance (sensitivity: 88.7±0.9%, and specificity: 91±1%) and the classification accuracy from subject-based fisher WPD-CSP is increased by 6-12% and 14%, respectively. The proposed subject-based fisher WPD-CSP method can not only remedy disadvantages of CSP by WPD but also discriminate
-
Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information
Directory of Open Access Journals (Sweden)
Kunlin Cao
2012-01-01
Full Text Available Accurate pulmonary image registration is a challenging problem when the lungs have a deformation with large distance. In this work, we present a nonrigid volumetric registration algorithm to track lung motion between a pair of intrasubject CT images acquired at different inflation levels and introduce a new vesselness similarity cost that improves intensity-only registration. Volumetric CT datasets from six human subjects were used in this study. The performance of four intensity-only registration algorithms was compared with and without adding the vesselness similarity cost function. Matching accuracy was evaluated using landmarks, vessel tree, and fissure planes. The Jacobian determinant of the transformation was used to reveal the deformation pattern of local parenchymal tissue. The average matching error for intensity-only registration methods was on the order of 1 mm at landmarks and 1.5 mm on fissure planes. After adding the vesselness preserving cost function, the landmark and fissure positioning errors decreased approximately by 25% and 30%, respectively. The vesselness cost function effectively helped improve the registration accuracy in regions near thoracic cage and near the diaphragm for all the intensity-only registration algorithms tested and also helped produce more consistent and more reliable patterns of regional tissue deformation.
-
Soufan, Othman
2012-09-01
Feature selection is the first task of any learning approach that is applied in major fields of biomedical, bioinformatics, robotics, natural language processing and social networking. In feature subset selection problem, a search methodology with a proper criterion seeks to find the best subset of features describing data (relevance) and achieving better performance (optimality). Wrapper approaches are feature selection methods which are wrapped around a classification algorithm and use a performance measure to select the best subset of features. We analyze the proper design of the objective function for the wrapper approach and highlight an objective based on several classification algorithms. We compare the wrapper approaches to different feature selection methods based on distance and information based criteria. Significant improvement in performance, computational time, and selection of minimally sized feature subsets is achieved by combining different objectives for the wrapper model. In addition, considering various classification methods in the feature selection process could lead to a global solution of desirable characteristics.
-
Zhou, Ruojing; Mou, Weimin
2016-08-01
Cognitive mapping is assumed to be through hippocampus-dependent place learning rather than striatum-dependent response learning. However, we proposed that either type of spatial learning, as long as it involves encoding metric relations between locations and reference points, could lead to a cognitive map. Furthermore, the fewer reference points to specify individual locations, the more accurate a cognitive map of these locations will be. We demonstrated that participants have more accurate representations of vectors between 2 locations and of configurations among 3 locations when locations are individually encoded in terms of a single landmark than when locations are encoded in terms of a boundary. Previous findings have shown that learning locations relative to a boundary involve stronger place learning and higher hippocampal activation whereas learning relative to a single landmark involves stronger response learning and higher striatal activation. Recognizing this, we have provided evidence challenging the cognitive map theory but favoring our proposal. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
-
Integrative approaches to the prediction of protein functions based on the feature selection
Directory of Open Access Journals (Sweden)
Lee Hyunju
2009-12-01
Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among
-
Directory of Open Access Journals (Sweden)
Mahdi Javanmardi
2017-09-01
Full Text Available Various applications have utilized a mobile mapping system (MMS as the main 3D urban remote sensing platform. However, the accuracy and precision of the three-dimensional data acquired by an MMS is highly dependent on the performance of the vehicle’s self-localization, which is generally performed by high-end global navigation satellite system (GNSS/inertial measurement unit (IMU integration. However, GNSS/IMU positioning quality degrades significantly in dense urban areas with high-rise buildings, which block and reflect the satellite signals. Traditional landmark updating methods, which improve MMS accuracy by measuring ground control points (GCPs and manually identifying those points in the data, are both labor-intensive and time-consuming. In this paper, we propose a novel and comprehensive framework for automatically georeferencing MMS data by capitalizing on road features extracted from high-resolution aerial surveillance data. The proposed framework has three key steps: (1 extracting road features from the MMS and aerial data; (2 obtaining Gaussian mixture models from the extracted aerial road features; and (3 performing registration of the MMS data to the aerial map using a dynamic sliding window and the normal distribution transform (NDT. The accuracy of the proposed framework is verified using field data, demonstrating that it is a reliable solution for high-precision urban mapping.
-
Quantitative Comparison of Tolerance-Based Feature Transforms
Reniers, Dennie; Telea, Alexandru
2006-01-01
Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary
-
Outline-based morphometrics, an overlooked method in arthropod studies?
Dujardin, Jean-Pierre; Kaba, D; Solano, P; Dupraz, M; McCoy, K D; Jaramillo-O, N
2014-12-01
Modern methods allow a geometric representation of forms, separating size and shape. In entomology, as well as in many other fields involving arthropod studies, shape variation has proved useful for species identification and population characterization. In medical entomology, it has been applied to very specific questions such as population structure, reinfestation of insecticide-treated areas and cryptic species recognition. For shape comparisons, great importance is given to the quality of landmarks in terms of comparability. Two conceptually and statistically separate approaches are: (i) landmark-based morphometrics, based on the relative position of a few anatomical "true" or "traditional" landmarks, and (ii) outline-based morphometrics, which captures the contour of forms through a sequence of close "pseudo-landmarks". Most of the studies on insects of medical, veterinary or economic importance make use of the landmark approach. The present survey makes a case for the outline method, here based on elliptic Fourier analysis. The collection of pseudo-landmarks may require the manual digitization of many points and, for this reason, might appear less attractive. It, however, has the ability to compare homologous organs or structures having no landmarks at all. This strength offers the possibility to study a wider range of anatomical structures and thus, a larger range of arthropods. We present a few examples highlighting its interest for separating close or cryptic species, or characterizing conspecific geographic populations, in a series of different vector organisms. In this simple application, i.e. the recognition of close or cryptic forms, the outline approach provided similar scores as those obtained by the landmark-based approach. Copyright © 2014 Elsevier B.V. All rights reserved.
-
Additivity of Feature-based and Symmetry-based Grouping Effects in Multiple Object Tracking
Directory of Open Access Journals (Sweden)
Chundi eWang
2016-05-01
Full Text Available Multiple object tracking (MOT is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the laws of perceptual organization proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. Additive effect refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The where and what pathways might have played an important role in the additive grouping effect.
-
Feature selection gait-based gender classification under different circumstances
Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah
2014-05-01
This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.
-
A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features
Directory of Open Access Journals (Sweden)
LEI Xiaoqi
2016-02-01
Full Text Available Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds(semi-automatic extraction,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features,is proposed in this paper.Firstly,the image is segmented,and then the linear and curve roads are obtained by using several object shape features,so the method that just only extract linear roads are rectified.Secondly,the step of road extraction is carried out based on the region growth,the road seeds are automatic selected and the road network is extracted.Finally,the extracted roads are regulated by combining the edge information.In experiments,the images that including the better gray uniform of road and the worse illuminated of road surface were chosen,and the results prove that the method of this study is promising.
-
Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali
2015-01-01
In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.
-
Bonmati, Ester; Hu, Yipeng; Gibson, Eli; Uribarri, Laura; Keane, Geri; Gurusami, Kurinchi; Davidson, Brian; Pereira, Stephen P; Clarkson, Matthew J; Barratt, Dean C
2018-06-01
Navigation of endoscopic ultrasound (EUS)-guided procedures of the upper gastrointestinal (GI) system can be technically challenging due to the small fields-of-view of ultrasound and optical devices, as well as the anatomical variability and limited number of orienting landmarks during navigation. Co-registration of an EUS device and a pre-procedure 3D image can enhance the ability to navigate. However, the fidelity of this contextual information depends on the accuracy of registration. The purpose of this study was to develop and test the feasibility of a simulation-based planning method for pre-selecting patient-specific EUS-visible anatomical landmark locations to maximise the accuracy and robustness of a feature-based multimodality registration method. A registration approach was adopted in which landmarks are registered to anatomical structures segmented from the pre-procedure volume. The predicted target registration errors (TREs) of EUS-CT registration were estimated using simulated visible anatomical landmarks and a Monte Carlo simulation of landmark localisation error. The optimal planes were selected based on the 90th percentile of TREs, which provide a robust and more accurate EUS-CT registration initialisation. The method was evaluated by comparing the accuracy and robustness of registrations initialised using optimised planes versus non-optimised planes using manually segmented CT images and simulated ([Formula: see text]) or retrospective clinical ([Formula: see text]) EUS landmarks. The results show a lower 90th percentile TRE when registration is initialised using the optimised planes compared with a non-optimised initialisation approach (p value [Formula: see text]). The proposed simulation-based method to find optimised EUS planes and landmarks for EUS-guided procedures may have the potential to improve registration accuracy. Further work will investigate applying the technique in a clinical setting.
-
TIBIAL LANDMARKS IN ACL ANATOMIC REPAIR
Directory of Open Access Journals (Sweden)
M. V. Demesсhenko
2016-01-01
Full Text Available Purpose: to identify anatomical landmarks on tibial articular surface to serve as reference in preparing tibial canal with respect to the center of ACL footprint during single bundle arthroscopic repair.Materials and methods. Twelve frozen knee joint specimens and 68 unpaired macerated human tibia were studied using anatomical, morphometric, statistical methods as well as graphic simulation.Results. Center of the tibial ACL footprint was located 13,1±1,7 mm anteriorly from posterior border of intercondylar eminence, at 1/3 of the distance along the line connecting apexes of internal and external tubercles and 6,1±0,5 mm anteriorly along the perpendicular raised to this point.Conclusion. Internal and external tubercles, as well as posterior border of intercondylar eminence can be considered as anatomical references to determine the center of the tibial ACL footprint and to prepare bone canals for anatomic ligament repair.
-
Directory of Open Access Journals (Sweden)
Neeraj Kumar Barnwal
2016-01-01
Full Text Available Background and Aims: The complications of central venous catheterisation can be minimized by ensuring catheter tip placement just above the superior vena cava-right atrium junction. We aimed to compare two methods, using an electrocardiogram (ECG or landmark as guides, for assessing correct depth of central venous catheter (CVC placement. Methods: In a prospective randomised study of sixty patients of <12 years of age, thirty patients each were allotted randomly to two groups (ECG and landmark. After induction, central venous catheterisation was performed by either of the two techniques and position of CVC tip was compared in post-operative chest X-ray with respect to carina. Unpaired t-test was used for quantitative data and Chi-square test was used for qualitative data. Results: In ECG group, positions of CVC tip were above carina in 12, at carina in 9 and below carina in 9 patients. In landmark group, the positions of CVC tips were above carina in 10, at carina in 4 and below carina in 16 patients. Mean distance of CVC tip in ECG group was 0.34 ± 0.23 cm and 0.66 ± 0.35 cm in landmark group (P = 0.0001. Complications occurred in one patient in ECG group and in nine patients in landmark group (P = 0.0056. Conclusion: Overall, landmark-guided technique was comparable with ECG technique. ECG-guided technique was more precise for CVC tip placement closer to carina. The incidence of complications was more in the landmark group.
-
Negahdar, Mohammadreza; Zacarias, Albert; Milam, Rebecca A.; Dunlap, Neal; Woo, Shiao Y.; Amini, Amir A.
2012-03-01
The treatment plan evaluation for lung cancer patients involves pre-treatment and post-treatment volume CT imaging of the lung. However, treatment of the tumor volume lung results in structural changes to the lung during the course of treatment. In order to register the pre-treatment volume to post-treatment volume, there is a need to find robust and homologous features which are not affected by the radiation treatment along with a smooth deformation field. Since airways are well-distributed in the entire lung, in this paper, we propose use of airway tree bifurcations for registration of the pre-treatment volume to the post-treatment volume. A dedicated and automated algorithm has been developed that finds corresponding airway bifurcations in both images. To derive the 3-D deformation field, a B-spline transformation model guided by mutual information similarity metric was used to guarantee the smoothness of the transformation while combining global information from bifurcation points. Therefore, the approach combines both global statistical intensity information with local image feature information. Since during normal breathing, the lung undergoes large nonlinear deformations, it is expected that the proposed method would also be applicable to large deformation registration between maximum inhale and maximum exhale images in the same subject. The method has been evaluated by registering 3-D CT volumes at maximum exhale data to all the other temporal volumes in the POPI-model data.
-
Image Recommendation Algorithm Using Feature-Based Collaborative Filtering
Kim, Deok-Hwan
As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.
-
Directory of Open Access Journals (Sweden)
Günther Grabner
2017-06-01
Full Text Available Background and Objective: Image-guided neurosurgery uses information from a wide spectrum of methods to inform the neurosurgeon's judgement about which tissue to resect and which to spare. Imaging data are registered to the patient's skull so that they correspond to the intraoperative macro- and microscopic view. The correspondence between imaging and optical systems breaks down during surgery, however, as a result of cerebro-spinal fluid drain age, tissue resection, and gravity-based brain shift. In this work we investigate whether a map of surface veins, automatically segmented from MRI, could serve as additional reference system.Methods: Gradient-echo based T2*-weighted imaging was performed on two human cadavers heads using a 7 Tesla MRI scanner. Automatic vessel segmentation was performed using the Frangi vesselness filter, and surface renderings of vessels compared with photographs of the surface of the brain following craniotomy.Results: A high level of correspondence was established between vessel maps and the post autopsy photographs. Corresponding veins, including the prominent superior anastomotic veins, could be identified in all brain lobes.Conclusion: Automatic surface vessel segmentation is feasible and the high correspondence to post autopsy photographs indicates that they could be used as an additional reference system for image-guided neurosurgery in order to maintain the correspondence between imaging and optical systems.This has the advantage over a skull-based reference system that veins are clearly visible to the surgeon and move and deform with the underlying tissue, potentially making this surface net of landmarks robust to brain shift.
-
Berona, Kristin; Abdi, Amin; Menchine, Michael; Mailhot, Tom; Kang, Tarina; Seif, Dina; Chilstrom, Mikaela
2017-02-01
The objectives of this study were to evaluate emergency medicine resident-performed ultrasound for diagnosis of effusions, compare the success of a landmark-guided (LM) approach with an ultrasound-guided (US) technique for hip, ankle and wrist arthrocentesis, and compare change in provider confidence with LM and US arthrocentesis. After a brief video on LM and US arthrocentesis, residents were asked to identify artificially created effusions in the hip, ankle and wrist in a cadaver model and to perform US and LM arthrocentesis of the effusions. Outcomes included success of joint aspiration, time to aspiration, and number of attempts. Residents were surveyed regarding their confidence in identifying effusions with ultrasound and performing LM and US arthrocentesis. Eighteen residents completed the study. Sensitivity of ultrasound for detecting joint effusion was 86% and specificity was 90%. Residents were successful with ultrasound in 96% of attempts and with landmark 89% of attempts (p=0.257). Median number of attempts was 1 with ultrasound and 2 with landmarks (p=0.12). Median time to success with ultrasound was 38s and 51s with landmarks (p=0.23). After the session, confidence in both US and LM arthrocentesis improved significantly, however the post intervention confidence in US arthrocentesis was higher than LM (4.3 vs. 3.8, p<0.001). EM residents were able to successfully identify joint effusions with ultrasound, however we were unable to detect significant differences in actual procedural success between the two modalities. Further studies are needed to define the role of ultrasound for arthrocentesis in the emergency department. Copyright © 2016 Elsevier Inc. All rights reserved.
-
Hortos, William S.
2008-04-01
Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at
-
Directory of Open Access Journals (Sweden)
A. A. Vorobeva
2017-01-01
Full Text Available The paper deals with identification and authentication of web users participating in the Internet information processes (based on features of online texts.In digital forensics web user identification based on various linguistic features can be used to discover identity of individuals, criminals or terrorists using the Internet to commit cybercrimes. Internet could be used as a tool in different types of cybercrimes (fraud and identity theft, harassment and anonymous threats, terrorist or extremist statements, distribution of illegal content and information warfare. Linguistic identification of web users is a kind of biometric identification, it can be used to narrow down the suspects, identify a criminal and prosecute him. Feature set includes various linguistic and stylistic features extracted from online texts. We propose dynamic feature selection for each web user identification task. Selection is based on calculating Manhattan distance to k-nearest neighbors (Relief-f algorithm. This approach improves the identification accuracy and minimizes the number of features. Experiments were carried out on several datasets with different level of class imbalance. Experiment results showed that features relevance varies in different set of web users (probable authors of some text; features selection for each set of web users improves identification accuracy by 4% at the average that is approximately 1% higher than with the use of static set of features. The proposed approach is most effective for a small number of training samples (messages per user.
-
2013-12-31
... consumer behavior; and questions about why comments on the Draft National Climate Assessment were not... Program for Consumer Products: Landmark Legal Foundation; Petition for Reconsideration AGENCY: Office of... Energy Consumers of America (IECA), American Gas Association (AGA), Cato Institute Center for Study of...
-
3-D FEATURE-BASED MATCHING BY RSTG APPROACH
Directory of Open Access Journals (Sweden)
J.-J. Jaw
2012-07-01
Full Text Available 3-D feature matching is the essential kernel in a fully automated feature-based LiDAR point cloud registration. After feasible procedures of feature acquisition, connecting corresponding features in different data frames is imperative to be solved. The objective addressed in this paper is developing an approach coined RSTG to retrieve corresponding counterparts of unsorted multiple 3-D features extracted from sets of LiDAR point clouds. RSTG stands for the four major processes, "Rotation alignment"; "Scale estimation"; "Translation alignment" and "Geometric check," strategically formulated towards finding out matching solution with high efficiency and leading to accomplishing the 3-D similarity transformation among all sets. The workable types of features to RSTG comprise points, lines, planes and clustered point groups. Each type of features can be employed exclusively or combined with others, if sufficiently supplied, throughout the matching scheme. The paper gives a detailed description of the matching methodology and discusses on the matching effects based on the statistical assessment which revealed that the RSTG approach reached an average matching rate of success up to 93% with around 6.6% of statistical type 1 error. Notably, statistical type 2 error, the critical indicator of matching reliability, was kept 0% throughout all the experiments.
-
Wang, Rui; Zhu, Zhengdan; Zhang, Liang
2015-05-01
Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.
-
Energy Technology Data Exchange (ETDEWEB)
Kim, Min Sun; Lee, Eun Joo; Lee, Jae Seo; Kang, Byung Cheock; Yoon, Suk Ja [Dental Science Research Institute, Chonnam National University, Gwangju (Korea, Republic of); Song, In Ja [Dept. of Nursing, Kwangju Women' s University, Gwangju (Korea, Republic of)
2015-12-15
The purpose of this study was to evaluate the influence of methods of establishing the midsagittal reference plane (MRP) on the locations of midfacial landmarks in the three-dimensional computed tomography (CT) analysis of facial asymmetry. A total of 24 patients (12 male and 12 female; mean age, 22.5 years; age range, 18.2-29.7 years) with facial asymmetry were included in this study. The MRP was established using two different methods on each patient's CT image. The x-coordinates of four midfacial landmarks (the menton, nasion, upper incisor, and lower incisor) were obtained by measuring the distance and direction of the landmarks from the MRP, and the two methods were compared statistically. The direction of deviation and the severity of asymmetry found using each method were also compared. The x-coordinates of the four anatomic landmarks all showed a statistically significant difference between the two methods of establishing the MRP. For the nasion and lower incisor, six patients (25.0%) showed a change in the direction of deviation. The severity of asymmetry also changed in 16 patients (66.7%). The results of this study suggest that the locations of midfacial landmarks change significantly according to the method used to establish the MRP.
-
Manouvakhova, Olga V; Macchi, Veronica; Fries, Fabian N; Loukas, Marios; De Caro, Raffaele; Oskouian, Rod J; Spinner, Robert J; Tubbs, R Shane
2018-02-01
Additional landmarks for identifying the suprascapular nerve at its entrance into the suprascapular foramen from an anterior approach would be useful to the surgeon. To identify landmarks for the identification of this hidden site within an anterior approach. In 8 adult cadavers (16 sides), lines were used to connect the superior angle of the scapula, the acromion, and the coracoid process tip thus creating an anatomic triangle. The suprascapular nerve's entrance into the suprascapular foramen was documented regarding its position within this anatomical triangle. Depths from the skin surface and specifically from the medial-most point of the clavicular attachment of the trapezius to the suprascapular nerve's entrance into the suprascapular foramen were measured using calipers and a ruler. The clavicle was then fractured and retracted superiorly to verify the position of the nerve's entrance into the suprascapular foramen. From the trapezius, the nerve's entrance into the foramen was 3 to 4.2 cm deep (mean, 3.5 cm). The mean distance from the tip of the corocoid process to the suprascapular foramen was 3.8 cm. The angle best used to approach the suprascapular foramen from the surface was 15° to 20°. Based on our study, an anterior suprascapular approach to the suprascapular nerve as it enters the suprascapular foramen can identify the most medial fibers of the trapezius attachment onto the clavicle and insert a finger at an angle of 15° to 20° laterally and advanced to an average depth of 3.5 cm. Copyright © 2017 by the Congress of Neurological Surgeons
-
RESEARCH ON REMOTE SENSING GEOLOGICAL INFORMATION EXTRACTION BASED ON OBJECT ORIENTED CLASSIFICATION
Directory of Open Access Journals (Sweden)
H. Gao
2018-04-01
Full Text Available The northern Tibet belongs to the Sub cold arid climate zone in the plateau. It is rarely visited by people. The geological working conditions are very poor. However, the stratum exposures are good and human interference is very small. Therefore, the research on the automatic classification and extraction of remote sensing geological information has typical significance and good application prospect. Based on the object-oriented classification in Northern Tibet, using the Worldview2 high-resolution remote sensing data, combined with the tectonic information and image enhancement, the lithological spectral features, shape features, spatial locations and topological relations of various geological information are excavated. By setting the threshold, based on the hierarchical classification, eight kinds of geological information were classified and extracted. Compared with the existing geological maps, the accuracy analysis shows that the overall accuracy reached 87.8561 %, indicating that the classification-oriented method is effective and feasible for this study area and provides a new idea for the automatic extraction of remote sensing geological information.
-
Integrated Phoneme Subspace Method for Speech Feature Extraction
Directory of Open Access Journals (Sweden)
Park Hyunsin
2009-01-01
Full Text Available Speech feature extraction has been a key focus in robust speech recognition research. In this work, we discuss data-driven linear feature transformations applied to feature vectors in the logarithmic mel-frequency filter bank domain. Transformations are based on principal component analysis (PCA, independent component analysis (ICA, and linear discriminant analysis (LDA. Furthermore, this paper introduces a new feature extraction technique that collects the correlation information among phoneme subspaces and reconstructs feature space for representing phonemic information efficiently. The proposed speech feature vector is generated by projecting an observed vector onto an integrated phoneme subspace (IPS based on PCA or ICA. The performance of the new feature was evaluated for isolated word speech recognition. The proposed method provided higher recognition accuracy than conventional methods in clean and reverberant environments.
-
Analysing co-articulation using frame-based feature trajectories
CSIR Research Space (South Africa)
Badenhorst, J
2010-11-01
Full Text Available The authors investigate several approaches aimed at a more detailed understanding of co-articulation in spoken utterances. They find that the Euclidean difference between instantaneous frame-based feature values and the mean values of these features...
-
New Informative Features for Fault Diagnosis of Industrial Systems by Supervised Classification
Verron , Sylvain; Tiplica , Teodor; Kobi , Abdessamad
2009-01-01
International audience; The purpose of this article is to present a method for industrial process diagnosis. We are interested in fault diagnosis considered as a supervised classication task. The interest of the proposed method is to take into account new features (and so new informations) in the classifier. These new features are probabilities extracted from a Bayesian network comparing the faulty observations to the normal operating conditions. The performances of this method are evaluated ...
-
Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina
2014-03-01
We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.
-
Fusion of geometric and texture features for finger knuckle surface recognition
Directory of Open Access Journals (Sweden)
K. Usha
2016-03-01
Full Text Available Hand-based biometrics plays a significant role in establishing security for real-time environments involving human interaction and is found to be more successful in terms of high speed and accuracy. This paper investigates on an integrated approach for personal authentication using Finger Back Knuckle Surface (FBKS based on two methodologies viz., Angular Geometric Analysis based Feature Extraction Method (AGFEM and Contourlet Transform based Feature Extraction Method (CTFEM. Based on these methods, this personal authentication system simultaneously extracts shape oriented feature information and textural pattern information of FBKS for authenticating an individual. Furthermore, the proposed geometric and textural analysis methods extract feature information from both proximal phalanx and distal phalanx knuckle regions (FBKS, while the existing works of the literature concentrate only on the features of proximal phalanx knuckle region. The finger joint region found nearer to the tip of the finger is called distal phalanx region of FBKS, which is a unique feature and has greater potentiality toward identification. Extensive experiments conducted using newly created database with 5400 FBKS images and the obtained results infer that the integration of shape oriented features with texture feature information yields excellent accuracy rate of 99.12% with lowest equal error rate of 1.04%.
-
Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.
Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao
2015-04-01
Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
-
Kaplan, Mustafa; Tanoglu, Alpaslan; Sakin, Yusuf Serdar; Akyol, Taner; Oncu, Kemal; Kara, Muammer; Yazgan, Yusuf
2016-12-01
There is still a debate about the exact measurement of the oesophagogastric junction and the diaphragmatic hiatus among clinicians. The aim of this study was to investigate the differences between landmark readings of gastroscopy on intubation and extubation, and to correlate these readings with a gastro-oesophageal reflux questionnaire. 116 cases who underwent diagnostic gastroscopy between January 2013 and June 2013 were included in this study. Landmark measurements were noted while withdrawing the endoscope and were also evaluated after the gastric air was fully emptied. We first used a frequency scale for the gastro-oesophageal reflux disease symptoms (FSSG) questionnaire in order to investigate dysmotility and acid reflux symptoms in the study population and correlated the FSSG questionnaire with intubation and extubation measurements at endoscopic examination. Mean age of included subjects was 49.41±17.7 (19-82) years. Males and females were equally represented. On FSSG scores, the total dysmotility score was 7.99±5.06 and the total score was 15.18±10.11. The difference between intubation and extubation measurements ranged from -3cm to +2cm (mean: -0.4). When an FSSG score of 30 was accepted as a cut-off value, we detected a significant difference between the measurements (p<0.05; t: 0.048). Accuracy of landmark measurements during gastroscopy is clearly affected from insertion or withdrawal of the endoscope. When differences in measurements between insertion and withdrawal were evident, comparable with the FSSG scores, the results became significantly different. In conclusion, according to FSSG scores, these measurements should be performed at the end of the endoscopy. Copyright © 2016 Pan-Arab Association of Gastroenterology. Published by Elsevier B.V. All rights reserved.
-
Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining
Directory of Open Access Journals (Sweden)
P. Kalaivani
2015-01-01
Full Text Available With the rapid growth of websites and web form the number of product reviews is available on the sites. An opinion mining system is needed to help the people to evaluate emotions, opinions, attitude, and behavior of others, which is used to make decisions based on the user preference. In this paper, we proposed an optimized feature reduction that incorporates an ensemble method of machine learning approaches that uses information gain and genetic algorithm as feature reduction techniques. We conducted comparative study experiments on multidomain review dataset and movie review dataset in opinion mining. The effectiveness of single classifiers Naïve Bayes, logistic regression, support vector machine, and ensemble technique for opinion mining are compared on five datasets. The proposed hybrid method is evaluated and experimental results using information gain and genetic algorithm with ensemble technique perform better in terms of various measures for multidomain review and movie reviews. Classification algorithms are evaluated using McNemar’s test to compare the level of significance of the classifiers.
-
Uniform competency-based local feature extraction for remote sensing images
Sedaghat, Amin; Mohammadi, Nazila
2018-01-01
Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.
-
Underwater Object Segmentation Based on Optical Features
Directory of Open Access Journals (Sweden)
Zhe Chen
2018-01-01
Full Text Available Underwater optical environments are seriously affected by various optical inputs, such as artificial light, sky light, and ambient scattered light. The latter two can block underwater object segmentation tasks, since they inhibit the emergence of objects of interest and distort image information, while artificial light can contribute to segmentation. Artificial light often focuses on the object of interest, and, therefore, we can initially identify the region of target objects if the collimation of artificial light is recognized. Based on this concept, we propose an optical feature extraction, calculation, and decision method to identify the collimated region of artificial light as a candidate object region. Then, the second phase employs a level set method to segment the objects of interest within the candidate region. This two-phase structure largely removes background noise and highlights the outline of underwater objects. We test the performance of the method with diverse underwater datasets, demonstrating that it outperforms previous methods.
-
Image segmentation-based robust feature extraction for color image watermarking
Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen
2018-04-01
This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.
-
A rapid extraction of landslide disaster information research based on GF-1 image
Wang, Sai; Xu, Suning; Peng, Ling; Wang, Zhiyi; Wang, Na
2015-08-01
In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 .Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.
-
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Directory of Open Access Journals (Sweden)
Rouzé Pierre
2004-05-01
Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.
-
Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso
Directory of Open Access Journals (Sweden)
Jin-Jia Wang
2015-01-01
Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.
-
Ma, Xin; Guo, Jing; Sun, Xiao
2016-01-01
DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.
-
Directory of Open Access Journals (Sweden)
Kyung-Min Lee
Full Text Available The purpose of this study was to investigate the influence of head motion on the accuracy of three-dimensional (3D reconstruction with cone-beam computed tomography (CBCT scan.Fifteen dry skulls were incorporated into a motion controller which simulated four types of head motion during CBCT scan: 2 horizontal rotations (to the right/to the left and 2 vertical rotations (upward/downward. Each movement was triggered to occur at the start of the scan for 1 second by remote control. Four maxillofacial surface models with head motion and one control surface model without motion were obtained for each skull. Nine landmarks were identified on the five maxillofacial surface models for each skull, and landmark identification errors were compared between the control model and each of the models with head motion.Rendered surface models with head motion were similar to the control model in appearance; however, the landmark identification errors showed larger values in models with head motion than in the control. In particular, the Porion in the horizontal rotation models presented statistically significant differences (P < .05. Statistically significant difference in the errors between the right and left side landmark was present in the left side rotation which was opposite direction to the scanner rotation (P < .05.Patient movement during CBCT scan might cause landmark identification errors on the 3D surface model in relation to the direction of the scanner rotation. Clinicians should take this into consideration to prevent patient movement during CBCT scan, particularly horizontal movement.
-
Weighted score-level feature fusion based on Dempster-Shafer evidence theory for action recognition
Zhang, Guoliang; Jia, Songmin; Li, Xiuzhi; Zhang, Xiangyin
2018-01-01
The majority of human action recognition methods use multifeature fusion strategy to improve the classification performance, where the contribution of different features for specific action has not been paid enough attention. We present an extendible and universal weighted score-level feature fusion method using the Dempster-Shafer (DS) evidence theory based on the pipeline of bag-of-visual-words. First, the partially distinctive samples in the training set are selected to construct the validation set. Then, local spatiotemporal features and pose features are extracted from these samples to obtain evidence information. The DS evidence theory and the proposed rule of survival of the fittest are employed to achieve evidence combination and calculate optimal weight vectors of every feature type belonging to each action class. Finally, the recognition results are deduced via the weighted summation strategy. The performance of the established recognition framework is evaluated on Penn Action dataset and a subset of the joint-annotated human metabolome database (sub-JHMDB). The experiment results demonstrate that the proposed feature fusion method can adequately exploit the complementarity among multiple features and improve upon most of the state-of-the-art algorithms on Penn Action and sub-JHMDB datasets.
-
Medland, A. J.; Zhu, Guowang; Gao, Jian; Sun, Jian
1996-03-01
Feature conversion, also called feature transformation and feature mapping, is defined as the process of converting features from one view of an object to another view of the object. In a relatively simple implementation, for each application the design features are automatically converted into features specific for that application. All modifications have to be made via the design features. This is the approach that has attracted most attention until now. In the ideal situation, however, conversions directly from application views to the design view, and to other applications views, are also possible. In this paper, some difficulties faced in feature conversion are discussed. A new representation scheme of feature-based parts models has been proposed for the purpose of one-way feature conversion. The parts models consist of five different levels of abstraction, extending from an assembly level and its attributes, single parts and their attributes, single features and their attributes, one containing the geometric reference element and finally one for detailed geometry. One implementation of feature conversion for rotational components within GT (Group Technology) has already been undertaken using an automated coding procedure operating on a design-feature database. This database has been generated by a feature-based design system, and the GT coding scheme used in this paper is a specific scheme created for a textile machine manufacturing plant. Such feature conversion techniques presented here are only in their early stages of development and further research is underway.
-
Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.
2018-04-01
In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.
-
Lambert, Anthony J; Wootton, Adrienne
2017-08-01
Different patterns of high density EEG activity were elicited by the same peripheral stimuli, in the context of Landmark Cueing and Perceptual Discrimination tasks. The C1 component of the visual event-related potential (ERP) at parietal - occipital electrode sites was larger in the Landmark Cueing task, and source localisation suggested greater activation in the superior parietal lobule (SPL) in this task, compared to the Perceptual Discrimination task, indicating stronger early recruitment of the dorsal visual stream. In the Perceptual Discrimination task, source localisation suggested widespread activation of the inferior temporal gyrus (ITG) and fusiform gyrus (FFG), structures associated with the ventral visual stream, during the early phase of the P1 ERP component. Moreover, during a later epoch (171-270ms after stimulus onset) increased temporal-occipital negativity, and stronger recruitment of ITG and FFG were observed in the Perceptual Discrimination task. These findings illuminate the contrasting functions of the dorsal and ventral visual streams, to support rapid shifts of attention in response to contextual landmarks, and conscious discrimination, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Brindal, Emily; Freyne, Jill; Saunders, Ian; Berkovsky, Shlomo; Smith, Greg; Noakes, Manny
2012-12-12
Obesity remains a serious issue in many countries. Web-based programs offer good potential for delivery of weight loss programs. Yet, many Internet-delivered weight loss studies include support from medical or nutritional experts, and relatively little is known about purely web-based weight loss programs. To determine whether supportive features and personalization in a 12-week web-based lifestyle intervention with no in-person professional contact affect retention and weight loss. We assessed the effect of different features of a web-based weight loss intervention using a 12-week repeated-measures randomized parallel design. We developed 7 sites representing 3 functional groups. A national mass media promotion was used to attract overweight/obese Australian adults (based on body mass index [BMI] calculated from self-reported heights and weights). Eligible respondents (n = 8112) were randomly allocated to one of 3 functional groups: information-based (n = 183), supportive (n = 3994), or personalized-supportive (n = 3935). Both supportive sites included tools, such as a weight tracker, meal planner, and social networking platform. The personalized-supportive site included a meal planner that offered recommendations that were personalized using an algorithm based on a user's preferences for certain foods. Dietary and activity information were constant across sites, based on an existing and tested 12-week weight loss program (the Total Wellbeing Diet). Before and/or after the intervention, participants completed demographic (including self-reported weight), behavioral, and evaluation questionnaires online. Usage of the website and features was objectively recorded. All screening and data collection procedures were performed online with no face-to-face contact. Across all 3 groups, attrition was high at around 40% in the first week and 20% of the remaining participants each week. Retention was higher for the supportive sites compared to the information-based site only
-
Mesbah, Mostefa; Balakrishnan, Malarvili; Colditz, Paul B.; Boashash, Boualem
2012-12-01
This article proposes a new method for newborn seizure detection that uses information extracted from both multi-channel electroencephalogram (EEG) and a single channel electrocardiogram (ECG). The aim of the study is to assess whether additional information extracted from ECG can improve the performance of seizure detectors based solely on EEG. Two different approaches were used to combine this extracted information. The first approach, known as feature fusion, involves combining features extracted from EEG and heart rate variability (HRV) into a single feature vector prior to feeding it to a classifier. The second approach, called classifier or decision fusion, is achieved by combining the independent decisions of the EEG and the HRV-based classifiers. Tested on recordings obtained from eight newborns with identified EEG seizures, the proposed neonatal seizure detection algorithms achieved 95.20% sensitivity and 88.60% specificity for the feature fusion case and 95.20% sensitivity and 94.30% specificity for the classifier fusion case. These results are considerably better than those involving classifiers using EEG only (80.90%, 86.50%) or HRV only (85.70%, 84.60%).
-
Directory of Open Access Journals (Sweden)
Nicole A Capela
Full Text Available Human activity recognition (HAR, using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter. The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree. Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.
-
Capela, Nicole A; Lemaire, Edward D; Baddour, Natalie
2015-01-01
Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.
-
O.M. Spirin; A.V. Iatsyshyn
2013-01-01
The paper analyzes the prerequisites for developing and becoming of new specialty 13.00.10 – information and communication technology in education. The features of training of the high-qualified specialists at the Institute of information technologies and learning tools of NAPS of Ukraine are examined. The subjects of dissertations on new specialty, are studied the respective research directions in new specialty are defined. The features of the formulation of scientific and categorical appara...
-
MRI features can predict EGFR expression in lower grade gliomas. A voxel-based radiomic analysis
Energy Technology Data Exchange (ETDEWEB)
Li, Yiming; Liu, Xing; Qian, Zenghui; Fan, Xing; Li, Shaowu; Jiang, Tao [Capital Medical University, Beijing Neurosurgical Institute, Beijing (China); Xu, Kaibin [Chinese Academy of Sciences, Institute of Automation, Beijing (China); Wang, Kai [Beijing Tiantan Hospital, Department of Neuroradiology, Beijing (China); Wang, Yinyan [Beijing Tiantan Hospital, Department of Neuroradiology, Beijing (China); Beijing Tiantan Hospital, Capital Medical University, Department of Neurosurgery, Beijing (China)
2018-01-15
To identify the magnetic resonance imaging (MRI) features associated with epidermal growth factor (EGFR) expression level in lower grade gliomas using radiomic analysis. 270 lower grade glioma patients with known EGFR expression status were randomly assigned into training (n=200) and validation (n=70) sets, and were subjected to feature extraction. Using a logistic regression model, a signature of MRI features was identified to be predictive of the EGFR expression level in lower grade gliomas in the training set, and the accuracy of prediction was assessed in the validation set. A signature of 41 MRI features achieved accuracies of 82.5% (area under the curve [AUC] = 0.90) in the training set and 90.0% (AUC = 0.95) in the validation set. This radiomic signature consisted of 25 first-order statistics or related wavelet features (including range, standard deviation, uniformity, variance), one shape and size-based feature (spherical disproportion), and 15 textural features or related wavelet features (including sum variance, sum entropy, run percentage). A radiomic signature allowing for the prediction of the EGFR expression level in patients with lower grade glioma was identified, suggesting that using tumour-derived radiological features for predicting genomic information is feasible. (orig.)
-
Communicating spatial information from verbal descriptions
Noordzij, M.L.
2005-01-01
Communication between people is difficult. A well-known example of this premise stems from asking directions in an unknown city. This can result in elaborate stories in which the narrator gives detailed and correct information concerning turns that need to be taken and landmarks that will be
-
A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.
Xue, Xiaoming; Zhou, Jianzhong
2017-01-01
To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
-
Directory of Open Access Journals (Sweden)
Cari Merkley
2010-12-01
Full Text Available Objective – To better understand music information seeking behaviour in a real life situation and to create a taxonomy relating to this behaviour to facilitate better comparison of music information retrieval studies in the future.Design – Content analysis of natural language queries.Setting – Google Answers, a fee based online service.Subjects – 1,705 queries and their related answers and comments posted in the music category of the Google Answers website before April 27, 2005.Methods – A total of 2,208 queries were retrieved from the music category on the Google Answers service. Google Answers was a fee based service in which users posted questions and indicated what they were willing to pay to have them answered. The queries selected for this study were posted prior to April 27, 2005, over a year before the service was discontinued completely. Of the 2208 queries taken from the site, only 1,705 were classified as relevant to the question of music information seeking by the researcher. The off-topic queries were not included in the study. Each of the 1,705 queries was coded according to the needs expressed by the user and the information provided to assist researchers in answering the question. The initial coding framework used by the researcher was informed by previous studies of music information retrieval to facilitate comparison, but was expanded and revised to reflect the evidence itself. Only the questions themselves were subjected to this iterative coding process. The answers provided by the Google Answer researchers and online comments posted by other users were examined by the author, but not coded for inclusion in the study.User needs in the questions were coded for their form and topic. Each question was assigned at least one form and one topic. Form refers to the type of question being asked and consisted of the following 10 categories: identification, location, verification, recommendation, evaluation, ready reference