Parameter Networks: Towards a Theory of Low-level Vision,

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1981-04-01

edge in image space arid increment those points in an array. Figure 5 shows the relevant geometry . Figure 5: Geometry for the I Iough Transform. In...8217Iels suc(h ,-s thiose shown in 1ligure 7 to reorganize origami wo.d- figures. Figoure?7. 1’o show an example In detail, Kender’s techn!Ciue for...Compuiter Science Dept, Carnegie-.Mcllon U., October 1979. Kanade, Tl., "A theory of Origami world," CMU-CS-78-144, Computer Science Dept, Carnegie

Kunstinäituselt Jumala ja kanade juurde ning sealt põrgusse / Riin Kübarsepp

Index Scriptorium Estoniae

Kübarsepp, Riin, 1978-

2005-01-01

Mirja-Mari Smidti ja Allan Tõnissoo näitus "Kunstinäitus" Hobusepea galeriis 31. III-18. IV. Tanel Saare "Gott und Huhn episode IV: seed shower" kuni 23. IV Draakoni galeriis. Kuni 24. IV Tallinna Linnagaleriis Pirjetta Branderi näitus "Põrgu ja teised jutud", millega oli kaasas Mikko Tuhkaneni kunstniku loomingu analüüsi sisaldav kirjutis "A Woman's work is never done"

Registration of retinal sequences from new video-ophthalmoscopic camera.

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Kolar, Radim; Tornow, Ralf P; Odstrcilik, Jan; Liberdova, Ivana

2016-05-20

Analysis of fast temporal changes on retinas has become an important part of diagnostic video-ophthalmology. It enables investigation of the hemodynamic processes in retinal tissue, e.g. blood-vessel diameter changes as a result of blood-pressure variation, spontaneous venous pulsation influenced by intracranial-intraocular pressure difference, blood-volume changes as a result of changes in light reflection from retinal tissue, and blood flow using laser speckle contrast imaging. For such applications, image registration of the recorded sequence must be performed. Here we use a new non-mydriatic video-ophthalmoscope for simple and fast acquisition of low SNR retinal sequences. We introduce a novel, two-step approach for fast image registration. The phase correlation in the first stage removes large eye movements. Lucas-Kanade tracking in the second stage removes small eye movements. We propose robust adaptive selection of the tracking points, which is the most important part of tracking-based approaches. We also describe a method for quantitative evaluation of the registration results, based on vascular tree intensity profiles. The achieved registration error evaluated on 23 sequences (5840 frames) is 0.78 ± 0.67 pixels inside the optic disc and 1.39 ± 0.63 pixels outside the optic disc. We compared the results with the commonly used approaches based on Lucas-Kanade tracking and scale-invariant feature transform, which achieved worse results. The proposed method can efficiently correct particular frames of retinal sequences for shift and rotation. The registration results for each frame (shift in X and Y direction and eye rotation) can also be used for eye-movement evaluation during single-spot fixation tasks.

Research on target tracking in coal mine based on optical flow method

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Xue, Hongye; Xiao, Qingwei

2015-03-01

To recognize, track and count the bolting machine in coal mine video images, a real-time target tracking method based on the Lucas-Kanade sparse optical flow is proposed in this paper. In the method, we judge whether the moving target deviate from its trajectory, predicate and correct the position of the moving target. The method solves the problem of failure to track the target or lose the target because of the weak light, uneven illumination and blocking. Using the VC++ platform and Opencv lib we complete the recognition and tracking. The validity of the method is verified by the result of the experiment.

Facial Expression Recognition Based on TensorFlow Platform

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Xia Xiao-Ling

2017-01-01

Full Text Available Facial expression recognition have a wide range of applications in human-machine interaction, pattern recognition, image understanding, machine vision and other fields. Recent years, it has gradually become a hot research. However, different people have different ways of expressing their emotions, and under the influence of brightness, background and other factors, there are some difficulties in facial expression recognition. In this paper, based on the Inception-v3 model of TensorFlow platform, we use the transfer learning techniques to retrain facial expression dataset (The Extended Cohn-Kanade dataset, which can keep the accuracy of recognition and greatly reduce the training time.

Static facial expression recognition with convolution neural networks

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Zhang, Feng; Chen, Zhong; Ouyang, Chao; Zhang, Yifei

2018-03-01

Facial expression recognition is a currently active research topic in the fields of computer vision, pattern recognition and artificial intelligence. In this paper, we have developed a convolutional neural networks (CNN) for classifying human emotions from static facial expression into one of the seven facial emotion categories. We pre-train our CNN model on the combined FER2013 dataset formed by train, validation and test set and fine-tune on the extended Cohn-Kanade database. In order to reduce the overfitting of the models, we utilized different techniques including dropout and batch normalization in addition to data augmentation. According to the experimental result, our CNN model has excellent classification performance and robustness for facial expression recognition.

Dynamic facial expression recognition based on geometric and texture features

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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.

Weighted Feature Gaussian Kernel SVM for Emotion Recognition.

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Wei, Wei; Jia, Qingxuan

2016-01-01

Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.

Implementation of the Lucas-Kanade image registration algorithm on a GPU for 3D computational platform stabilisation

CSIR Research Space (South Africa)

Duvenhage, B

2010-06-01

Full Text Available rate of 15 fps at an image and ROI size of 640 480 pixels. This result was measured on an NVidia Tesla C870 GPU with about half as many processor cores as the GeForce GTX285 GPU. Marzat, et al. however estimate that their execu- tion times would...

Active AU Based Patch Weighting for Facial Expression Recognition

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Weicheng Xie

2017-01-01

Full Text Available Facial expression has many applications in human-computer interaction. Although feature extraction and selection have been well studied, the specificity of each expression variation is not fully explored in state-of-the-art works. In this work, the problem of multiclass expression recognition is converted into triplet-wise expression recognition. For each expression triplet, a new feature optimization model based on action unit (AU weighting and patch weight optimization is proposed to represent the specificity of the expression triplet. The sparse representation-based approach is then proposed to detect the active AUs of the testing sample for better generalization. The algorithm achieved competitive accuracies of 89.67% and 94.09% for the Jaffe and Cohn–Kanade (CK+ databases, respectively. Better cross-database performance has also been observed.

IDENTIFICAÇÃO E RASTREAMENTO DE VEÍCULOS UTILIZANDO FLUXO ÓPTICO

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Fernando Souza Castro

2015-06-01

Full Text Available Controlling the traffic of vehicles is a very hard task to be realized. It is represents a challenge in the search for solutions that can help control and vehicle traffic monitoring on roads. In this work we consider the use of the differential method, proposed by Lucas and Kanade, to estimate the optical flow, such as computational tool to track and classify vehicles from video frame by frame. The vehicles are found in each frame are classified by its size: small, medium and large. The results of this work can be applied, for example, in systems of count of vehicles in highways. Another use for this work, which is a high value, would be to construct intelligent traffic lights, which control the block and freedom of the pathway based on the flow of vehicles.

Facial Expression Recognition from Video Sequences Based on Spatial-Temporal Motion Local Binary Pattern and Gabor Multiorientation Fusion Histogram

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Lei Zhao

2017-01-01

Full Text Available This paper proposes novel framework for facial expressions analysis using dynamic and static information in video sequences. First, based on incremental formulation, discriminative deformable face alignment method is adapted to locate facial points to correct in-plane head rotation and break up facial region from background. Then, spatial-temporal motion local binary pattern (LBP feature is extracted and integrated with Gabor multiorientation fusion histogram to give descriptors, which reflect static and dynamic texture information of facial expressions. Finally, a one-versus-one strategy based multiclass support vector machine (SVM classifier is applied to classify facial expressions. Experiments on Cohn-Kanade (CK + facial expression dataset illustrate that integrated framework outperforms methods using single descriptors. Compared with other state-of-the-art methods on CK+, MMI, and Oulu-CASIA VIS datasets, our proposed framework performs better.

Markerless Augmented Reality via Stereo Video See-Through Head-Mounted Display Device

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Chung-Hung Hsieh

2015-01-01

Full Text Available Conventionally, the camera localization for augmented reality (AR relies on detecting a known pattern within the captured images. In this study, a markerless AR scheme has been designed based on a Stereo Video See-Through Head-Mounted Display (HMD device. The proposed markerless AR scheme can be utilized for medical applications such as training, telementoring, or preoperative explanation. Firstly, a virtual model for AR visualization is aligned to the target in physical space by an improved Iterative Closest Point (ICP based surface registration algorithm, with the target surface structure reconstructed by a stereo camera pair; then, a markerless AR camera localization method is designed based on the Kanade-Lucas-Tomasi (KLT feature tracking algorithm and the Random Sample Consensus (RANSAC correction algorithm. Our AR camera localization method is shown to be better than the traditional marker-based and sensor-based AR environment. The demonstration system was evaluated with a plastic dummy head and the display result is satisfactory for a multiple-view observation.

A General Purpose Feature Extractor for Light Detection and Ranging Data

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Edwin B. Olson

2010-11-01

Full Text Available Feature extraction is a central step of processing Light Detection and Ranging (LIDAR data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset.

A general purpose feature extractor for light detection and ranging data.

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Li, Yangming; Olson, Edwin B

2010-01-01

Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature, specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset.

Automatic Quadcopter Control Avoiding Obstacle Using Camera with Integrated Ultrasonic Sensor

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Anis, Hanafi; Haris Indra Fadhillah, Ahmad; Darma, Surya; Soekirno, Santoso

2018-04-01

Automatic navigation on the drone is being developed these days, a wide variety of types of drones and its automatic functions. Drones used in this study was an aircraft with four propellers or quadcopter. In this experiment, image processing used to recognize the position of an object and ultrasonic sensor used to detect obstacle distance. The method used to trace an obsctacle in image processing was the Lucas-Kanade-Tomasi Tracker, which had been widely used due to its high accuracy. Ultrasonic sensor used to complement the image processing success rate to be fully detected object. The obstacle avoidance system was to observe at the program decisions from some obstacle conditions read by the camera and ultrasonic sensors. Visual feedback control based PID controllers are used as a control of drones movement. The conclusion of the obstacle avoidance system was to observe at the program decisions from some obstacle conditions read by the camera and ultrasonic sensors.

Laser Spot Tracking Based on Modified Circular Hough Transform and Motion Pattern Analysis

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Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-01-01

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas–Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development. PMID:25350502

Laser spot tracking based on modified circular Hough transform and motion pattern analysis.

Science.gov (United States)

Krstinić, Damir; Skelin, Ana Kuzmanić; Milatić, Ivan

2014-10-27

Laser pointers are one of the most widely used interactive and pointing devices in different human-computer interaction systems. Existing approaches to vision-based laser spot tracking are designed for controlled indoor environments with the main assumption that the laser spot is very bright, if not the brightest, spot in images. In this work, we are interested in developing a method for an outdoor, open-space environment, which could be implemented on embedded devices with limited computational resources. Under these circumstances, none of the assumptions of existing methods for laser spot tracking can be applied, yet a novel and fast method with robust performance is required. Throughout the paper, we will propose and evaluate an efficient method based on modified circular Hough transform and Lucas-Kanade motion analysis. Encouraging results on a representative dataset demonstrate the potential of our method in an uncontrolled outdoor environment, while achieving maximal accuracy indoors. Our dataset and ground truth data are made publicly available for further development.

Convolutional neural networks with balanced batches for facial expressions recognition

Science.gov (United States)

Battini Sönmez, Elena; Cangelosi, Angelo

2017-03-01

This paper considers the issue of fully automatic emotion classification on 2D faces. In spite of the great effort done in recent years, traditional machine learning approaches based on hand-crafted feature extraction followed by the classification stage failed to develop a real-time automatic facial expression recognition system. The proposed architecture uses Convolutional Neural Networks (CNN), which are built as a collection of interconnected processing elements to simulate the brain of human beings. The basic idea of CNNs is to learn a hierarchical representation of the input data, which results in a better classification performance. In this work we present a block-based CNN algorithm, which uses noise, as data augmentation technique, and builds batches with a balanced number of samples per class. The proposed architecture is a very simple yet powerful CNN, which can yield state-of-the-art accuracy on the very competitive benchmark algorithm of the Extended Cohn Kanade database.

Estimation of water flow velocity in small plants using cold neutron imaging with D 2O tracer

Science.gov (United States)

Matsushima, U.; Herppich, W. B.; Kardjilov, N.; Graf, W.; Hilger, A.; Manke, I.

2009-06-01

Water flow imaging may help to better understand various problems related to water stress of plants. It may help to fully understand the water relations of plants. The objective of this research was to estimate the velocity of water flow in plant samples. Cut roses ( Rosa hybrida, var. 'Milva') were used as samples. Cold neutron radiography (CNR) was conducted at CONRAD, Helmholtz Center Berlin for Materials and Energy, Berlin, Germany. D 2O and H 2O were interchangeably injected into the water feeding system of the sample. After the uptake of D 2O, the neutron transmission increased due to the smaller attenuation coefficient of D 2O compared to H 2O. Replacement of D 2O in the rose peduncle was clearly observed. Three different optical flow algorithms, Block Matching, Horn-Schunck and Lucas-Kanade, were used to calculate the vector of D 2O tracer flow. The quality of sequential images providing sufficient spatial and temporal resolution allowed to estimate flow vector.

Emotion recognition based on multiple order features using fractional Fourier transform

Science.gov (United States)

Ren, Bo; Liu, Deyin; Qi, Lin

2017-07-01

In order to deal with the insufficiency of recently algorithms based on Two Dimensions Fractional Fourier Transform (2D-FrFT), this paper proposes a multiple order features based method for emotion recognition. Most existing methods utilize the feature of single order or a couple of orders of 2D-FrFT. However, different orders of 2D-FrFT have different contributions on the feature extraction of emotion recognition. Combination of these features can enhance the performance of an emotion recognition system. The proposed approach obtains numerous features that extracted in different orders of 2D-FrFT in the directions of x-axis and y-axis, and uses the statistical magnitudes as the final feature vectors for recognition. The Support Vector Machine (SVM) is utilized for the classification and RML Emotion database and Cohn-Kanade (CK) database are used for the experiment. The experimental results demonstrate the effectiveness of the proposed method.

System for face recognition under expression variations of neutral-sampled individuals using recognized expression warping and a virtual expression-face database

Science.gov (United States)

Petpairote, Chayanut; Madarasmi, Suthep; Chamnongthai, Kosin

2018-01-01

The practical identification of individuals using facial recognition techniques requires the matching of faces with specific expressions to faces from a neutral face database. A method for facial recognition under varied expressions against neutral face samples of individuals via recognition of expression warping and the use of a virtual expression-face database is proposed. In this method, facial expressions are recognized and the input expression faces are classified into facial expression groups. To aid facial recognition, the virtual expression-face database is sorted into average facial-expression shapes and by coarse- and fine-featured facial textures. Wrinkle information is also employed in classification by using a process of masking to adjust input faces to match the expression-face database. We evaluate the performance of the proposed method using the CMU multi-PIE, Cohn-Kanade, and AR expression-face databases, and we find that it provides significantly improved results in terms of face recognition accuracy compared to conventional methods and is acceptable for facial recognition under expression variation.

Dictionaries of Canadian English

Directory of Open Access Journals (Sweden)

John Considine

2011-10-01

Full Text Available

Abstract: The lexicographical record of English in Canada began with wordlists of the late eighteenth, nineteenth, and early twentieth centuries. From the beginning of the twentieth century onwards, the general vocabulary of English in Canada has been represented in bilingual and monolingual dictionaries, often adapted from American or British dictionaries. In the 1950s, several important projects were initiated, resulting in the publication of general dictionaries of English in Canada, and of dictionaries of Canadianisms and of the vocabulary of particular regions of Can-ada. This article gives an overview of these dictionaries and of their reception, contextualizing them in the larger picture of the lexicography of Canada's other official language, French, and of a number of its non-official languages. It concludes by looking at the future of English-language lexicography in Canada, and by observing that although it has, at its best, reached a high degree of sophistication, there are still major opportunities waiting to be taken.

Keywords: DICTIONARY, LEXICOGRAPHY, CANADIAN ENGLISH, CANADIANISMS, NATIONAL DICTIONARIES, CANADIAN FRENCH, CANADIAN FIRST NATIONS LAN-GUAGES, BILINGUAL DICTIONARIES, REGIONAL DICTIONARIES, UNFINISHED DICTIONARY PROJECTS

Opsomming: Woordeboeke van Kanadese Engels. Die leksikografiese optekening van Engels in Kanada begin met woordelyste van die laat agtiende, neëntiende en vroeë twintigste eeue. Van die begin van die twintigste eeu af en verder, is die algemene woordeskat van Engels weergegee in tweetalige en eentalige woordeboeke, dikwels met wysiginge ontleen aan Ameri-kaanse en Britse woordeboeke. In die 1950's is verskeie belangrike projekte onderneem wat gelei het tot die publikasie van algemene woordeboeke van Engels in Kanada, en van woordeboeke van Kanadeïsmes en van die woordeskat van bepaalde streke van Kanada. Hierdie artikel gee 'n oorsig van dié woordeboeke, en van hul ontvangs, deur

An Improved Brain-Inspired Emotional Learning Algorithm for Fast Classification

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Ying Mei

2017-06-01

Full Text Available Classification is an important task of machine intelligence in the field of information. The artificial neural network (ANN is widely used for classification. However, the traditional ANN shows slow training speed, and it is hard to meet the real-time requirement for large-scale applications. In this paper, an improved brain-inspired emotional learning (BEL algorithm is proposed for fast classification. The BEL algorithm was put forward to mimic the high speed of the emotional learning mechanism in mammalian brain, which has the superior features of fast learning and low computational complexity. To improve the accuracy of BEL in classification, the genetic algorithm (GA is adopted for optimally tuning the weights and biases of amygdala and orbitofrontal cortex in the BEL neural network. The combinational algorithm named as GA-BEL has been tested on eight University of California at Irvine (UCI datasets and two well-known databases (Japanese Female Facial Expression, Cohn–Kanade. The comparisons of experiments indicate that the proposed GA-BEL is more accurate than the original BEL algorithm, and it is much faster than the traditional algorithm.

A simple, remote, video based breathing monitor.

Science.gov (United States)

Regev, Nir; Wulich, Dov

2017-07-01

Breathing monitors have become the all-important cornerstone of a wide variety of commercial and personal safety applications, ranging from elderly care to baby monitoring. Many such monitors exist in the market, some, with vital signs monitoring capabilities, but none remote. This paper presents a simple, yet efficient, real time method of extracting the subject's breathing sinus rhythm. Points of interest are detected on the subject's body, and the corresponding optical flow is estimated and tracked using the well known Lucas-Kanade algorithm on a frame by frame basis. A generalized likelihood ratio test is then utilized on each of the many interest points to detect which is moving in harmonic fashion. Finally, a spectral estimation algorithm based on Pisarenko harmonic decomposition tracks the harmonic frequency in real time, and a fusion maximum likelihood algorithm optimally estimates the breathing rate using all points considered. The results show a maximal error of 1 BPM between the true breathing rate and the algorithm's calculated rate, based on experiments on two babies and three adults.

Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

Science.gov (United States)

Kachach, Redouane; Cañas, José María

2016-05-01

Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

Automatic Human Facial Expression Recognition Based on Integrated Classifier From Monocular Video with Uncalibrated Camera

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Yu Tao

2017-01-01

Full Text Available An automatic recognition framework for human facial expressions from a monocular video with an uncalibrated camera is proposed. The expression characteristics are first acquired from a kind of deformable template, similar to a facial muscle distribution. After associated regularization, the time sequences from the trait changes in space-time under complete expressional production are then arranged line by line in a matrix. Next, the matrix dimensionality is reduced by a method of manifold learning of neighborhood-preserving embedding. Finally, the refined matrix containing the expression trait information is recognized by a classifier that integrates the hidden conditional random field (HCRF and support vector machine (SVM. In an experiment using the Cohn–Kanade database, the proposed method showed a comparatively higher recognition rate than the individual HCRF or SVM methods in direct recognition from two-dimensional human face traits. Moreover, the proposed method was shown to be more robust than the typical Kotsia method because the former contains more structural characteristics of the data to be classified in space-time

Facial expression recognition based on weber local descriptor and sparse representation

Science.gov (United States)

Ouyang, Yan

2018-03-01

Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.

Proposed patient motion monitoring system using feature point tracking with a web camera.

Science.gov (United States)

Miura, Hideharu; Ozawa, Shuichi; Matsuura, Takaaki; Yamada, Kiyoshi; Nagata, Yasushi

2017-12-01

Patient motion monitoring systems play an important role in providing accurate treatment dose delivery. We propose a system that utilizes a web camera (frame rate up to 30 fps, maximum resolution of 640 × 480 pixels) and an in-house image processing software (developed using Microsoft Visual C++ and OpenCV). This system is simple to use and convenient to set up. The pyramidal Lucas-Kanade method was applied to calculate motions for each feature point by analysing two consecutive frames. The image processing software employs a color scheme where the defined feature points are blue under stable (no movement) conditions and turn red along with a warning message and an audio signal (beeping alarm) for large patient movements. The initial position of the marker was used by the program to determine the marker positions in all the frames. The software generates a text file that contains the calculated motion for each frame and saves it as a compressed audio video interleave (AVI) file. We proposed a patient motion monitoring system using a web camera, which is simple and convenient to set up, to increase the safety of treatment delivery.

An ISVD-based Euclidian structure from motion for smartphones

Science.gov (United States)

Masiero, A.; Guarnieri, A.; Vettore, A.; Pirotti, F.

2014-06-01

The development of Mobile Mapping systems over the last decades allowed to quickly collect georeferenced spatial measurements by means of sensors mounted on mobile vehicles. Despite the large number of applications that can potentially take advantage of such systems, because of their cost their use is currently typically limited to certain specialized organizations, companies, and Universities. However, the recent worldwide diffusion of powerful mobile devices typically embedded with GPS, Inertial Navigation System (INS), and imaging sensors is enabling the development of small and compact mobile mapping systems. More specifically, this paper considers the development of a 3D reconstruction system based on photogrammetry methods for smartphones (or other similar mobile devices). The limited computational resources available in such systems and the users' request for real time reconstructions impose very stringent requirements on the computational burden of the 3D reconstruction procedure. This work takes advantage of certain recently developed mathematical tools (incremental singular value decomposition) and of photogrammetry techniques (structure from motion, Tomasi-Kanade factorization) to access very computationally efficient Euclidian 3D reconstruction of the scene. Furthermore, thanks to the presence of instrumentation for localization embedded in the device, the obtained 3D reconstruction can be properly georeferenced.

Facial expression recognition under partial occlusion based on fusion of global and local features

Science.gov (United States)

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.

Automatic analysis of ciliary beat frequency using optical flow

Science.gov (United States)

Figl, Michael; Lechner, Manuel; Werther, Tobias; Horak, Fritz; Hummel, Johann; Birkfellner, Wolfgang

2012-02-01

Ciliary beat frequency (CBF) can be a useful parameter for diagnosis of several diseases, as e.g. primary ciliary dyskinesia. (PCD). CBF computation is usually done using manual evaluation of high speed video sequences, a tedious, observer dependent, and not very accurate procedure. We used the OpenCV's pyramidal implementation of the Lukas-Kanade algorithm for optical flow computation and applied this to certain objects to follow the movements. The objects were chosen by their contrast applying the corner detection by Shi and Tomasi. Discrimination between background/noise and cilia by a frequency histogram allowed to compute the CBF. Frequency analysis was done using the Fourier transform in matlab. The correct number of Fourier summands was found by the slope in an approximation curve. The method showed to be usable to distinguish between healthy and diseased samples. However there remain difficulties in automatically identifying the cilia, and also in finding enough high contrast cilia in the image. Furthermore the some of the higher contrast cilia are lost (and sometimes found) by the method, an easy way to distinguish the correct sub-path of a point's path have yet to be found in the case where the slope methods doesn't work.

Facial Emotion Recognition System – A Machine Learning Approach

Science.gov (United States)

Ramalingam, V. V.; Pandian, A.; Jayakumar, Lavanya

2018-04-01

Frown is a medium for people correlation and it could be exercised in multiple real systems. Single crucial stage for frown realizing is to exactly select hysterical aspects. This journal proposed a frown realization scheme applying transformative Particle Swarm Optimization (PSO) based aspect accumulation. This entity initially employs changed LVP, handles crisscross adjacent picture element contrast, for achieving the selective first frown portrayal. Then the PSO entity inserted with a concept of micro Genetic Algorithm (mGA) called mGA-embedded PSO designed for achieving aspect accumulation. This study, the technique subsumes no disposable memory, a little-populace insignificant flock, a latest acceleration that amends with the approach and a sub dimension-based in-depth local frown aspect examines. Assistance of provincial utilization and comprehensive inspection examine structure of alleviating of an immature concurrence complication of conventional PSO. Numerous identifiers are used to diagnose different frown expositions. Stationed on extensive study within and other-sphere pictures from the continued Cohn Kanade and MMI benchmark directory appropriately. Determination of the application exceeds most advanced level PSO variants, conventional PSO, classical GA and alternate relevant frown realization structures is described with powerful limit. Extending our accession to a motion based FER application for connecting patch-based Gabor aspects with continuous data in multi-frames.

Non-rigid estimation of cell motion in calcium time-lapse images

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Hachi, Siham; Lucumi Moreno, Edinson; Desmet, An-Sofie; Vanden Berghe, Pieter; Fleming, Ronan M. T.

2016-03-01

Calcium imaging is a widely used technique in neuroscience permitting the simultaneous monitoring of electro- physiological activity of hundreds of neurons at single cell resolution. Identification of neuronal activity requires rapid and reliable image analysis techniques, especially when neurons fire and move simultaneously over time. Traditionally, image segmentation is performed to extract individual neurons in the first frame of a calcium sequence. Thereafter, the mean intensity is calculated from the same region of interest in each frame to infer calcium signals. However, when cells move, deform and fire, this segmentation on its own generates artefacts and therefore biased neuronal activity. Therefore, there is a pressing need to develop a more efficient cell tracking technique. We hereby present a novel vision-based cell tracking scheme using a thin-plate spline deformable model. The thin-plate spline warping is based on control points detected using the Fast from Accelerated Segment Test descriptor and tracked using the Lucas-Kanade optical flow. Our method is able to track neurons in calcium time-series, even when there are large changes in intensity, such as during a firing event. The robustness and efficiency of the proposed approach is validated on real calcium time-lapse images of a neuronal population.

KARATE WITH CONSTRUCTIVE LEARNING

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Srikrishna Karanam

2012-02-01

Full Text Available Any conventional learning process involves the traditional hierarchy of garnering of information and then recall gathered information. Constructive learning is an important research area having wide impact on teaching methods in education, learning theories, and plays a major role in many education reform movements. It is observed that constructive learning advocates the interconnection between emotions and learning. Human teachers identify the emotions of students with varying degrees of accuracy and can improve the learning rate of the students by motivating them. In learning with computers, computers also should be given the capability to recognize emotions so as to optimize the learning process. Image Processing is a very popular tool used in the process of establishing the theory of Constructive Learning. In this paper we use the Optical Flow computation in image sequences to analyze the accuracy of the moves of a karate player. We have used the Lucas-Kanade method for computing the optical flow in image sequences. A database consisting of optical flow images by a group of persons learning karate is formed and the learning rates are analyzed in order to main constructive learning. The contours of flow images are compared with the standard images and the error graphs are plotted. Analysis of the emotion of the amateur karate player is made by observing the error plots.

Robust infrared target tracking using discriminative and generative approaches

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Asha, C. S.; Narasimhadhan, A. V.

2017-09-01

The process of designing an efficient tracker for thermal infrared imagery is one of the most challenging tasks in computer vision. Although a lot of advancement has been achieved in RGB videos over the decades, textureless and colorless properties of objects in thermal imagery pose hard constraints in the design of an efficient tracker. Tracking of an object using a single feature or a technique often fails to achieve greater accuracy. Here, we propose an effective method to track an object in infrared imagery based on a combination of discriminative and generative approaches. The discriminative technique makes use of two complementary methods such as kernelized correlation filter with spatial feature and AdaBoost classifier with pixel intesity features to operate in parallel. After obtaining optimized locations through discriminative approaches, the generative technique is applied to determine the best target location using a linear search method. Unlike the baseline algorithms, the proposed method estimates the scale of the target by Lucas-Kanade homography estimation. To evaluate the proposed method, extensive experiments are conducted on 17 challenging infrared image sequences obtained from LTIR dataset and a significant improvement of mean distance precision and mean overlap precision is accomplished as compared with the existing trackers. Further, a quantitative and qualitative assessment of the proposed approach with the state-of-the-art trackers is illustrated to clearly demonstrate an overall increase in performance.

Increasing feasibility of the field-programmable gate array implementation of an iterative image registration using a kernel-warping algorithm

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Nguyen, An Hung; Guillemette, Thomas; Lambert, Andrew J.; Pickering, Mark R.; Garratt, Matthew A.

2017-09-01

Image registration is a fundamental image processing technique. It is used to spatially align two or more images that have been captured at different times, from different sensors, or from different viewpoints. There have been many algorithms proposed for this task. The most common of these being the well-known Lucas-Kanade (LK) and Horn-Schunck approaches. However, the main limitation of these approaches is the computational complexity required to implement the large number of iterations necessary for successful alignment of the images. Previously, a multi-pass image interpolation algorithm (MP-I2A) was developed to considerably reduce the number of iterations required for successful registration compared with the LK algorithm. This paper develops a kernel-warping algorithm (KWA), a modified version of the MP-I2A, which requires fewer iterations to successfully register two images and less memory space for the field-programmable gate array (FPGA) implementation than the MP-I2A. These reductions increase feasibility of the implementation of the proposed algorithm on FPGAs with very limited memory space and other hardware resources. A two-FPGA system rather than single FPGA system is successfully developed to implement the KWA in order to compensate insufficiency of hardware resources supported by one FPGA, and increase parallel processing ability and scalability of the system.

Hybrid markerless tracking of complex articulated motion in golf swings.

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Fung, Sim Kwoh; Sundaraj, Kenneth; Ahamed, Nizam Uddin; Kiang, Lam Chee; Nadarajah, Sivadev; Sahayadhas, Arun; Ali, Md Asraf; Islam, Md Anamul; Palaniappan, Rajkumar

2014-04-01

Sports video tracking is a research topic that has attained increasing attention due to its high commercial potential. A number of sports, including tennis, soccer, gymnastics, running, golf, badminton and cricket have been utilised to display the novel ideas in sports motion tracking. The main challenge associated with this research concerns the extraction of a highly complex articulated motion from a video scene. Our research focuses on the development of a markerless human motion tracking system that tracks the major body parts of an athlete straight from a sports broadcast video. We proposed a hybrid tracking method, which consists of a combination of three algorithms (pyramidal Lucas-Kanade optical flow (LK), normalised correlation-based template matching and background subtraction), to track the golfer's head, body, hands, shoulders, knees and feet during a full swing. We then match, track and map the results onto a 2D articulated human stick model to represent the pose of the golfer over time. Our work was tested using two video broadcasts of a golfer, and we obtained satisfactory results. The current outcomes of this research can play an important role in enhancing the performance of a golfer, provide vital information to sports medicine practitioners by providing technically sound guidance on movements and should assist to diminish the risk of golfing injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN from a Geostationary Satellite.

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Yu Liu

Full Text Available The prediction of the short-term quantitative precipitation nowcasting (QPN from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC; the Horn-Schunck optical-flow scheme (PHS; and the Pyramid Lucas-Kanade Optical Flow method (PPLK, which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6. The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

Science.gov (United States)

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

2015-01-01

The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

A dynamic texture-based approach to recognition of facial actions and their temporal models.

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Koelstra, Sander; Pantic, Maja; Patras, Ioannis

2010-11-01

In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the dynamics and the appearance in the face region of an input video are compared: an extended version of Motion History Images and a novel method based on Nonrigid Registration using Free-Form Deformations (FFDs). The extracted motion representation is used to derive motion orientation histogram descriptors in both the spatial and temporal domain. Per AU, a combination of discriminative, frame-based GentleBoost ensemble learners and dynamic, generative Hidden Markov Models detects the presence of the AU in question and its temporal segments in an input image sequence. When tested for recognition of all 27 lower and upper face AUs, occurring alone or in combination in 264 sequences from the MMI facial expression database, the proposed method achieved an average event recognition accuracy of 89.2 percent for the MHI method and 94.3 percent for the FFD method. The generalization performance of the FFD method has been tested using the Cohn-Kanade database. Finally, we also explored the performance on spontaneous expressions in the Sensitive Artificial Listener data set.

Pose-invariant face recognition using Markov random fields.

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Ho, Huy Tho; Chellappa, Rama

2013-04-01

One of the key challenges for current face recognition techniques is how to handle pose variations between the probe and gallery face images. In this paper, we present a method for reconstructing the virtual frontal view from a given nonfrontal face image using Markov random fields (MRFs) and an efficient variant of the belief propagation algorithm. In the proposed approach, the input face image is divided into a grid of overlapping patches, and a globally optimal set of local warps is estimated to synthesize the patches at the frontal view. A set of possible warps for each patch is obtained by aligning it with images from a training database of frontal faces. The alignments are performed efficiently in the Fourier domain using an extension of the Lucas-Kanade algorithm that can handle illumination variations. The problem of finding the optimal warps is then formulated as a discrete labeling problem using an MRF. The reconstructed frontal face image can then be used with any face recognition technique. The two main advantages of our method are that it does not require manually selected facial landmarks or head pose estimation. In order to improve the performance of our pose normalization method in face recognition, we also present an algorithm for classifying whether a given face image is at a frontal or nonfrontal pose. Experimental results on different datasets are presented to demonstrate the effectiveness of the proposed approach.

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera.

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Ci, Wenyan; Huang, Yingping

2016-10-17

Visual odometry estimates the ego-motion of an agent (e.g., vehicle and robot) using image information and is a key component for autonomous vehicles and robotics. This paper proposes a robust and precise method for estimating the 6-DoF ego-motion, using a stereo rig with optical flow analysis. An objective function fitted with a set of feature points is created by establishing the mathematical relationship between optical flow, depth and camera ego-motion parameters through the camera's 3-dimensional motion and planar imaging model. Accordingly, the six motion parameters are computed by minimizing the objective function, using the iterative Levenberg-Marquard method. One of key points for visual odometry is that the feature points selected for the computation should contain inliers as much as possible. In this work, the feature points and their optical flows are initially detected by using the Kanade-Lucas-Tomasi (KLT) algorithm. A circle matching is followed to remove the outliers caused by the mismatching of the KLT algorithm. A space position constraint is imposed to filter out the moving points from the point set detected by the KLT algorithm. The Random Sample Consensus (RANSAC) algorithm is employed to further refine the feature point set, i.e., to eliminate the effects of outliers. The remaining points are tracked to estimate the ego-motion parameters in the subsequent frames. The approach presented here is tested on real traffic videos and the results prove the robustness and precision of the method.

Waste management '05; Entsorgung '05

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-07-01

The pocket book comprises two sections. The first part discusses waste management issues in Germany: Refuse-derived fuels, emission trading, domestic waste management market, separate collecting of the biogenic waste fraction, waste management in Canada, the Belgian system Recupel for electric and electronic scrap, contracting and energy efficiency, treatment of organic waste in the EU, industrial safety, Deutsche Bundesstiftung Umwelt (DBU), funding of environmental projects, recycling and utilisation, renewables in new products, quality assurance. Part 2 contains data and figures of the waste management industry: Waste market, data of waste management organisations, waste volumes of the federal states, disposal and recycling, waste wood, water management, members of the BDE and its regional associations, press departments, European associations, authorities, environmental consulting, research institutions, energy agencies, journals. (uke) [German] Das Taschenbuch gliedert sich in 2 Teile. Der 1. Teile eroertert Themen der Entsorgungswirtschaft in Deutschland: Einsatz von Sekundaerbrennstoffen, Emissionshandel, Abfallwirtschaft im Binnenmarkt, Anspruch auf Beibehaltung der getrennten Bioabfall-Erfassung, Abfallwirtschaft und Abfallentsorgung in Kanade, das belgische System Recupelzur Sammlung und Entsorgungvon Elektro- und Electronik-Altgeraeten, Contracting und Energieeffizienz, Behandlung organische Abfaelle in der EU, Arbeitssicherheit, Deutsche Bundesstiftung Umwelt (DBU) Umweltfoerderung, Kreislaufwirtschaft, Recycling von Stoffstroemen und Einsatz nachwachsender Rohstoffe in neuen Produkten, Qualitaetsicherung. Im 2. Teil werden Daten und Zahlen der Entsorgungswirtschaft zusammengetragen: Abfallmarkt, Wirtschaftsdaten der Unternehmen, Abfallmengen in den Bundeslaendern, Entsorgung und Verwertung, Altholz, Wasserwirtschaft, Mitglieder des BDE und seiner Regionalverbaende, Pressestellen, europaeische Fachverbaende, Behoerden

Non-mydriatic video ophthalmoscope to measure fast temporal changes of the human retina

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Tornow, Ralf P.; Kolář, Radim; Odstrčilík, Jan

2015-07-01

The analysis of fast temporal changes of the human retina can be used to get insight to normal physiological behavior and to detect pathological deviations. This can be important for the early detection of glaucoma and other eye diseases. We developed a small, lightweight, USB powered video ophthalmoscope that allows taking video sequences of the human retina with at least 25 frames per second without dilating the pupil. Short sequences (about 10 s) of the optic nerve head (20° x 15°) are recorded from subjects and registered offline using two-stage process (phase correlation and Lucas-Kanade approach) to compensate for eye movements. From registered video sequences, different parameters can be calculated. Two applications are described here: measurement of (i) cardiac cycle induced pulsatile reflection changes and (ii) eye movements and fixation pattern. Cardiac cycle induced pulsatile reflection changes are caused by changing blood volume in the retina. Waveform and pulse parameters like amplitude and rise time can be measured in any selected areas within the retinal image. Fixation pattern ΔY(ΔX) can be assessed from eye movements during video acquisition. The eye movements ΔX[t], ΔY[t] are derived from image registration results with high temporal (40 ms) and spatial (1,86 arcmin) resolution. Parameters of pulsatile reflection changes and fixation pattern can be affected in beginning glaucoma and the method described here may support early detection of glaucoma and other eye disease.

A fast position estimation method for a control rod guide tube inspection robot with a single camera

International Nuclear Information System (INIS)

Lee, Jae C.; Seop, Jun H.; Choi, Yu R.; Kim, Jae H.

2004-01-01

One of the problems in the inspection of control rod guide tubes using a mobile robot is accurate estimation of the robot's position. The problem is usually explained by the question 'Where am I?'. We can solve this question by a method called dead reckoning using odometers. But it has some inherent drawbacks such that the position error grows without bound unless an independent reference is used periodically to reduce the errors. In this paper, we presented one method to overcome this drawback by using a vision sensor. Our method is based on the classical Lucas Kanade algorithm for on image tracking. In this algorithm, an optical flow must be calculated at every image frame, thus it has intensive computing load. In order to handle large motions, it is preferable to use a large integration window. But a small integration window is more preferable to keep the details contained in the images. We used the robot's movement information obtained from the dead reckoning as an input parameter for the feature tracking algorithm in order to restrict the position of an integration window. By means of this method, we could reduce the size of an integration window without any loss of its ability to handle large motions and could avoid the trade off in the accuracy. And we could estimate the position of our robot relatively fast without on intensive computing time and the inherent drawbacks mentioned above. We studied this algorithm for applying it to the control rod guide tubes inspection robot and tried an inspection without on operator's intervention

A nowcasting technique based on application of the particle filter blending algorithm

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Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

A study of coronary artery rotational motion with dense scale-space optical flow in intravascular ultrasound

Energy Technology Data Exchange (ETDEWEB)

Danilouchkine, M G; Mastik, F; Steen, A F W van der [Department of Biomedical Engineering, Erasmus Medical Center, Ee2302, PO Box 2040, 3000 CA, Rotterdam (Netherlands)], E-mail: m.danilouchkine@ErasmusMC.nl, E-mail: f.mastik@ErasmusMC.nl, E-mail: a.vandersteen@ErasmusMC.nl

2009-03-21

This paper describes a novel method for estimating tissue motion in two-dimensional intravascular ultrasound (IVUS) images of a coronary artery. It is based on the classical Lukas-Kanade (LK) algorithm for optical flow (OF). The OF vector field quantifies the amount of misalignment between two consecutive frames in a sequence of images. From the theoretical standpoint, two fundamental improvements are proposed in this paper. First, using a simplified representation of the vessel wall as a medium with randomly distributed scatterers, it was shown that the OF equation satisfies the integral brightness conservation law. Second, a scale-space embedding for the OF equation was derived under the assumption of spatial consistency in IVUS acquisitions. The spatial coherence is equivalent to a locally affine motion model. The latter effectively captures and appropriately describes a complex deformation pattern of the coronary vessel wall under the varying physiological conditions (i.e. pulsatile blood pressure). The accuracy of OF tracking was estimated on the tissue-mimicking phantoms subjected to the controlled amount of angular deviation. Moreover, the performance of the classical LK and proposed approach was compared using the simulated IVUS images with an atherosclerotic lesion. The experimental results showed robust and reliable performance of up to 5{sup 0} of rotation, which is within the plausible range of circumferential displacement of the coronary arteries. Subsequently, the algorithm was used to analyze vessel wall motion in 18 IVUS pullbacks from 16 patients. The in vivo experiments revealed that the motion of coronary arteries is primarily determined by the cardiac contraction.

Determination of feature generation methods for PTZ camera object tracking

Science.gov (United States)

Doyle, Daniel D.; Black, Jonathan T.

2012-06-01

Object detection and tracking using computer vision (CV) techniques have been widely applied to sensor fusion applications. Many papers continue to be written that speed up performance and increase learning of artificially intelligent systems through improved algorithms, workload distribution, and information fusion. Military application of real-time tracking systems is becoming more and more complex with an ever increasing need of fusion and CV techniques to actively track and control dynamic systems. Examples include the use of metrology systems for tracking and measuring micro air vehicles (MAVs) and autonomous navigation systems for controlling MAVs. This paper seeks to contribute to the determination of select tracking algorithms that best track a moving object using a pan/tilt/zoom (PTZ) camera applicable to both of the examples presented. The select feature generation algorithms compared in this paper are the trained Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the Mixture of Gaussians (MoG) background subtraction method, the Lucas- Kanade optical flow method (2000) and the Farneback optical flow method (2003). The matching algorithm used in this paper for the trained feature generation algorithms is the Fast Library for Approximate Nearest Neighbors (FLANN). The BSD licensed OpenCV library is used extensively to demonstrate the viability of each algorithm and its performance. Initial testing is performed on a sequence of images using a stationary camera. Further testing is performed on a sequence of images such that the PTZ camera is moving in order to capture the moving object. Comparisons are made based upon accuracy, speed and memory.

Effectiveness of an Automatic Tracking Software in Underwater Motion Analysis

Directory of Open Access Journals (Sweden)

Fabrício A. Magalhaes

2013-12-01

Full Text Available Tracking of markers placed on anatomical landmarks is a common practice in sports science to perform the kinematic analysis that interests both athletes and coaches. Although different software programs have been developed to automatically track markers and/or features, none of them was specifically designed to analyze underwater motion. Hence, this study aimed to evaluate the effectiveness of a software developed for automatic tracking of underwater movements (DVP, based on the Kanade-Lucas-Tomasi feature tracker. Twenty-one video recordings of different aquatic exercises (n = 2940 markers’ positions were manually tracked to determine the markers’ center coordinates. Then, the videos were automatically tracked using DVP and a commercially available software (COM. Since tracking techniques may produce false targets, an operator was instructed to stop the automatic procedure and to correct the position of the cursor when the distance between the calculated marker’s coordinate and the reference one was higher than 4 pixels. The proportion of manual interventions required by the software was used as a measure of the degree of automation. Overall, manual interventions were 10.4% lower for DVP (7.4% than for COM (17.8%. Moreover, when examining the different exercise modes separately, the percentage of manual interventions was 5.6% to 29.3% lower for DVP than for COM. Similar results were observed when analyzing the type of marker rather than the type of exercise, with 9.9% less manual interventions for DVP than for COM. In conclusion, based on these results, the developed automatic tracking software presented can be used as a valid and useful tool for underwater motion analysis.

Vares ja kana : [valmid] / Ivan Krõlov ; tlk. Eduard Kansa, Mart Raud, Timotheos Kuusik, Johannes Semper, G. Õis, Arnold Tulik, Oskar Urgart, Jaan Kärner, Jakob Tamm, Erni Hiir

Index Scriptorium Estoniae

Krõlov, Ivan, 1768(1769)-1844

2006-01-01

Sisu: Vares ja Kana ; Moosekandid ; Vares ja Rebane ; Konn ja Härg ; Pirtsakas Näitsik ; Oraakel ; Rukkilill ; Tuli ja Metsatukk ; Hunt ja Talleke ; Pärdik ja Prillid ; Ahvid ; Tihane ; Eesel ; Kotkas ja Kanad ; Võimumees ja Mõttetark ; Koerte sõprus ; Kasujaotus ; Vaat ; Kvartett ; Teekäijad ja Koerad ; Hunt penilas ; Oja ; Rebane ja Mäger ; Rohutirts ja Sipelgas ; Luiskaja ; Kukk ja Pärlitera ; Jänes jahil ; Hunt ja Kägu ; Haug ja Kass ; Peremees ja Sulane ; Voor ; Elevant maavalitsejaks ; Eesel ja Ööbik ; Külamehe kimbatus ; Elevant ja Mops ; Hunt ja tema Kutsikas ; Kass ja Kokk ; Lõvi ja Sääsk ; Aednik ja Filosoof ; Haned ; Siga ; Vanamees ja kolm noorukit ; Kotkas ja Ämblik ; Lehed ja Juured ; Hunt ja Rebane ; Lohe ; Rästas ; Mehhaanik ; Trishka satter ; Tiik ja Jõgi ; Luik, Haug ja Vähk ; Erak ja Karu ; Mesilane ja Kärbsed ; Lõvi jahisaak ; Talupojad ja Jõgi ; Lilled ; Uudishimulik ; Kaastundlik Rebane ; Kogukonna koosolek ; Demjani kalasupp ; Tihane ja Tuvi ; Hiir ja Rott ; Peegel ja Ahv ; Sääsk ja Karjane ; Talupoeg ja Surm ; Hunt ja Karjased ; Lõvi ja Rebane ; Kamm ; Hunt ja Kurg ; Pilv ; Poiss ja Siug ; Maamees ja Siug ; Kägu ja Tuvike ; Kaks Vaati ; Töökas Karu ; Rebane ja Viinamarjad ; Karu võrgus ; Kirjamees ja Röövel ; Mölder ; Siga Tamme all ; Kärbes ja Mesilane ; Ämblik ja Mesilane ; Rebane ja Eesel ; Siug ja Talleke ; Ööbikud ; Peremes ja Lammas ; Kaks Külameest ; Kaks Koera ; Kass ja Ööbik ; Kalade tants ; Haug ; Habemenoad ; Hiired ; Hunt ja Kass ; Karjane ; Orav ; Damaskuse mõõk ; Koer ja Hobune ; Rebane ; Hundid ja Lambad ; Kägu ja Kukk

Caracterización de unidades de acción facial combinando métodos kernel y análisis de componentes independientes

Directory of Open Access Journals (Sweden)

Damián Alberto Álvarez

2010-01-01

Full Text Available El trabajo descrito en este documento presenta una metodología para la caracterización de unidades de acción facial (AUs, que representan cambios sutiles de las expresiones faciales. La metodología se basa en métodos Kernel, para realizar un mapeo no lineal de los datos y buscar las direcciones de las proyecciones de los datos en el espacio característico mediante análisis de componentes independientes (ICA. La validación se realiza sobre la base de datos Cohn-Kanade. Se hace un preprocesamiento de las imágenes a través de ecualización del histograma, un blanqueamiento de los datos con análisis de componentes principales basado en Kernel (KPCA, de esta forma el mapeo en el espacio característico busca una estructura lineal de los datos de entrada, finalmente se aplica ICA para hacer que la distribución de los datos proyectados sea lo menos Gaussiana posible. El desempeño alcanzado fue del 96.64% ±0.54 de exactitud para el reconocimiento promedio de tres combinaciones de AUs del rostro entero más rostros neutrales, se detectan principalmente cambios que ocurren entre transiciones rápidas de AUs que se manifiestan de forma instantánea. Adicionalmente la metodología planteada permite reducir el tamaño del espacio característico ya que se representan los datos en términos únicamente de sus componentes independientes (ICs de tal manera que se utilizan tan solo las variables que aportan mayor información, lo que permite disminuir la complejidad del clasificador.

Ultrasound assessment of fascial connectivity in the lower limb during maximal cervical flexion: technical aspects and practical application of automatic tracking.

Science.gov (United States)

Cruz-Montecinos, Carlos; Cerda, Mauricio; Sanzana-Cuche, Rodolfo; Martín-Martín, Jaime; Cuesta-Vargas, Antonio

2016-01-01

The fascia provides and transmits forces for connective tissues, thereby regulating human posture and movement. One way to assess the myofascial interaction is a fascia ultrasound recording. Ultrasound can follow fascial displacement either manually or automatically through two-dimensional (2D) method. One possible method is the iterated Lucas-Kanade Pyramid (LKP) algorithm, which is based on automatic pixel tracking during passive movements in 2D fascial displacement assessments. Until now, the accumulated error over time has not been considered, even though it could be crucial for detecting fascial displacement in low amplitude movements. The aim of this study was to assess displacement of the medial gastrocnemius fascia during cervical spine flexion in a kyphotic posture with the knees extended and ankles at 90°. The ultrasound transducer was placed on the extreme dominant belly of the medial gastrocnemius. Displacement was calculated from nine automatically selected tracking points. To determine cervical flexion, an established 2D marker protocol was implemented. Offline pressure sensors were used to synchronize the 2D kinematic data from cervical flexion and deep fascia displacement of the medial gastrocnemius. Fifteen participants performed the cervical flexion task. The basal tracking error was 0.0211 mm. In 66 % of the subjects, a proximal fascial tissue displacement of the fascia above the basal error (0.076 mm ± 0.006 mm) was measured. Fascia displacement onset during cervical spine flexion was detected over 70 % of the cycle; however, only when detected for more than 80 % of the cycle was displacement considered statistically significant as compared to the first 10 % of the cycle (ANOVA, p < 0.05). By using an automated tracking method, the present analyses suggest statistically significant displacement of deep fascia. Further studies are needed to corroborate and fully understand the mechanisms associated with these results.

Image navigation and registration for the geostationary lightning mapper (GLM)

Science.gov (United States)

van Bezooijen, Roel W. H.; Demroff, Howard; Burton, Gregory; Chu, Donald; Yang, Shu S.

2016-10-01

The Geostationary Lightning Mappers (GLM) for the Geostationary Operational Environmental Satellite (GOES) GOES-R series will, for the first time, provide hemispherical lightning information 24 hours a day from longitudes of 75 and 137 degrees west. The first GLM of a series of four is planned for launch in November, 2016. Observation of lightning patterns by GLM holds promise to improve tornado warning lead times to greater than 20 minutes while halving the present false alarm rates. In addition, GLM will improve airline traffic flow management, and provide climatology data allowing us to understand the Earth's evolving climate. The paper describes the method used for translating the pixel position of a lightning event to its corresponding geodetic longitude and latitude, using the J2000 attitude of the GLM mount frame reported by the spacecraft, the position of the spacecraft, and the alignment of the GLM coordinate frame relative to its mount frame. Because the latter alignment will experience seasonal variation, this alignment is determined daily using GLM background images collected over the previous 7 days. The process involves identification of coastlines in the background images and determination of the alignment change necessary to match the detected coastline with the coastline predicted using the GSHHS database. Registration is achieved using a variation of the Lucas-Kanade algorithm where we added a dither and average technique to improve performance significantly. An innovative water mask technique was conceived to enable self-contained detection of clear coastline sections usable for registration. Extensive simulations using accurate visible images from GOES13 and GOES15 have been used to demonstrate the performance of the coastline registration method, the results of which are presented in the paper.

Compute-unified device architecture implementation of a block-matching algorithm for multiple graphical processing unit cards.

Science.gov (United States)

Massanes, Francesc; Cadennes, Marie; Brankov, Jovan G

2011-07-01

In this paper we describe and evaluate a fast implementation of a classical block matching motion estimation algorithm for multiple Graphical Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) computing engine. The implemented block matching algorithm (BMA) uses summed absolute difference (SAD) error criterion and full grid search (FS) for finding optimal block displacement. In this evaluation we compared the execution time of a GPU and CPU implementation for images of various sizes, using integer and non-integer search grids.The results show that use of a GPU card can shorten computation time by a factor of 200 times for integer and 1000 times for a non-integer search grid. The additional speedup for non-integer search grid comes from the fact that GPU has built-in hardware for image interpolation. Further, when using multiple GPU cards, the presented evaluation shows the importance of the data splitting method across multiple cards, but an almost linear speedup with a number of cards is achievable.In addition we compared execution time of the proposed FS GPU implementation with two existing, highly optimized non-full grid search CPU based motion estimations methods, namely implementation of the Pyramidal Lucas Kanade Optical flow algorithm in OpenCV and Simplified Unsymmetrical multi-Hexagon search in H.264/AVC standard. In these comparisons, FS GPU implementation still showed modest improvement even though the computational complexity of FS GPU implementation is substantially higher than non-FS CPU implementation.We also demonstrated that for an image sequence of 720×480 pixels in resolution, commonly used in video surveillance, the proposed GPU implementation is sufficiently fast for real-time motion estimation at 30 frames-per-second using two NVIDIA C1060 Tesla GPU cards.

Wave front sensing for next generation earth observation telescope

Science.gov (United States)

Delvit, J.-M.; Thiebaut, C.; Latry, C.; Blanchet, G.

2017-09-01

High resolution observations systems are highly dependent on optics quality and are usually designed to be nearly diffraction limited. Such a performance allows to set a Nyquist frequency closer to the cut off frequency, or equivalently to minimize the pupil diameter for a given ground sampling distance target. Up to now, defocus is the only aberration that is allowed to evolve slowly and that may be inflight corrected, using an open loop correction based upon ground estimation and refocusing command upload. For instance, Pleiades satellites defocus is assessed from star acquisitions and refocusing is done with a thermal actuation of the M2 mirror. Next generation systems under study at CNES should include active optics in order to allow evolving aberrations not only limited to defocus, due for instance to in orbit thermal variable conditions. Active optics relies on aberration estimations through an onboard Wave Front Sensor (WFS). One option is using a Shack Hartmann. The Shack-Hartmann wave-front sensor could be used on extended scenes (unknown landscapes). A wave-front computation algorithm should then be implemented on-board the satellite to provide the control loop wave-front error measure. In the worst case scenario, this measure should be computed before each image acquisition. A robust and fast shift estimation algorithm between Shack-Hartmann images is then needed to fulfill this last requirement. A fast gradient-based algorithm using optical flows with a Lucas-Kanade method has been studied and implemented on an electronic device developed by CNES. Measurement accuracy depends on the Wave Front Error (WFE), the landscape frequency content, the number of searched aberrations, the a priori knowledge of high order aberrations and the characteristics of the sensor. CNES has realized a full scale sensitivity analysis on the whole parameter set with our internally developed algorithm.

Active appearance pyramids for object parametrisation and fitting.

Science.gov (United States)

Zhang, Qiang; Bhalerao, Abhir; Dickenson, Edward; Hutchinson, Charles

2016-08-01

Object class representation is one of the key problems in various medical image analysis tasks. We propose a part-based parametric appearance model we refer to as an Active Appearance Pyramid (AAP). The parts are delineated by multi-scale Local Feature Pyramids (LFPs) for superior spatial specificity and distinctiveness. An AAP models the variability within a population with local translations of multi-scale parts and linear appearance variations of the assembly of the parts. It can fit and represent new instances by adjusting the shape and appearance parameters. The fitting process uses a two-step iterative strategy: local landmark searching followed by shape regularisation. We present a simultaneous local feature searching and appearance fitting algorithm based on the weighted Lucas and Kanade method. A shape regulariser is derived to calculate the maximum likelihood shape with respect to the prior and multiple landmark candidates from multi-scale LFPs, with a compact closed-form solution. We apply the 2D AAP on the modelling of variability in patients with lumbar spinal stenosis (LSS) and validate its performance on 200 studies consisting of routine axial and sagittal MRI scans. Intervertebral sagittal and parasagittal cross-sections are typically used for the diagnosis of LSS, we therefore build three AAPs on L3/4, L4/5 and L5/S1 axial cross-sections and three on parasagittal slices. Experiments show significant improvement in convergence range, robustness to local minima and segmentation precision compared with Constrained Local Models (CLMs), Active Shape Models (ASMs) and Active Appearance Models (AAMs), as well as superior performance in appearance reconstruction compared with AAMs. We also validate the performance on 3D CT volumes of hip joints from 38 studies. Compared to AAMs, AAPs achieve a higher segmentation and reconstruction precision. Moreover, AAPs have a significant improvement in efficiency, consuming about half the memory and less than 10% of

Non-contact flow gauging for the extension and development of rating curves

Science.gov (United States)

Perks, Matthew; Large, Andy; Russell, Andy

2015-04-01

Accurate measurement of river discharge is fundamental to understanding hydrological processes, associated hazards and ecological responses within fluvial systems. Established protocols for determining river discharge are partial, predominantly invasive and logistically difficult during high flows. There is demand for new methods for accurate quantification of flow velocity under high-flow/flood conditions to in turn enable better post-event reconstruction of peak discharge. As a consequence considerable effort has been devoted to the development of innovative technologies for the representation of flow in open channels. Remotely operated fixed and mobile systems capable of providing quantitative estimates of instantaneous and time-averaged flow characteristics using non-contact methods has been a major development. Amongst the new approaches for stand-alone continuous monitoring of surface flows is Large Scale Particle Image Velocimetry (LSPIV). Here we adapt the LSPIV concept, to provide continuous discharge measurements in non-uniform channels with complex flow conditions. High Definition videos (1080p; 30fps) of the water surface are acquired at 5 minute intervals. The image is rectified to correct for perspective distortion using a new, open source tool which minimises errors resulting from oblique image capture. Naturally occurring artefacts on the water surface (e.g. bubbles, debris, etc.) are tracked with the Kanade-Lucas-Tomasi (KLT) algorithm. The data generated is in the form of a complex surface water velocity field which can be interrogated to extract a range of hydrological information such as the streamwise velocity at a cross-section of interest, or even allow the interrogation of hydrodynamic flow structures. Here we demonstrate that this approach is capable of generating river discharge data comparable to concurrent measurements made using existing, accepted technologies (e.g. ADCP). The outcome is better constraint and extension of rating curves

TH-CD-206-08: An Anthropopathic Deformable Phantom for Geometric and Dose Accumulation Accuracy Validation of Deformable Image Registration

Energy Technology Data Exchange (ETDEWEB)

Liao, Y; Chen, H; Chen, J; Zhen, X; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China); Gu, X [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: To design and construct a three-dimensional (3D) anthropopathic abdominal phantom for evaluating deformable image registration (DIR) accuracy on images and dose deformation in adaptive radiation therapy (ART). Method: Organ moulds, including liver, kidney, spleen, stomach, vertebra and two metastasis tumors, are 3D printed using the contours from an ovarian cancer patient. The organ moulds are molded with deformable gels that made of different mixtures of polyvinyl chloride (PVC) and the softener dioctyl terephthalate. Gels with different densities are obtained by a polynomial fitting curve which describes the relation between the CT number and PVC-softener blending ratio. The rigid vertebras are constructed by moulding with white cement. The final abdominal phantom is assembled by arranging all the fabricated organs inside a hollow dummy according to their anatomies and sealed with deformable gel with averaged CT number of muscle and fat. Geometric and dosimetric landmarks are embedded inside the phantom for spatial accuracy and dose accumulation accuracy studies. Three DIR algorithms available in the open source DIR toolkit-DIRART, including the Demons, the Horn-Schunck and Lucas-Kanade method and the Level-Set Motion method, are tested using the constructed phantom. Results: Viscoelastic behavior is observed in the constructed deformable gel, which serves as an ideal material for the deformable phantom. The constructed abdominal phantom consists of highly realistic anatomy and the fabricated organs inside have close CT number to its reference patient. DIR accuracy studies conducted on the constructed phantom using three DIR approaches indicate that geometric accuracy of a DIR algorithm has achieved does not guarantee accuracy in dose accumulation. Conclusions: We have designed and constructed an anthropopathic abdominal deformable phantom with satisfactory elastic property, realistic organ density and anatomy. This physical phantom is recyclable and can

MO-G-18C-03: Evaluation of Deformable Image Registration for Lung Motion Estimation Using Hyperpolarized Gas Tagging MRI

International Nuclear Information System (INIS)

Huang, Q; Zhang, Y; Liu, Y; Hu, L; Yin, F; Cai, J; Miller, W

2014-01-01

Purpose: Hyperpolarized gas (HP) tagging MRI is a novel imaging technique for direct measurement of lung motion during breathing. This study aims to quantitatively evaluate the accuracy of deformable image registration (DIR) in lung motion estimation using HP tagging MRI as references. Methods: Three healthy subjects were imaged using the HP MR tagging, as well as a high-resolution 3D proton MR sequence (TrueFISP) at the end-of-inhalation (EOI) and the end-of-exhalation (EOE). Ground truth of lung motion and corresponding displacement vector field (tDVF) was derived from HP tagging MRI by manually tracking the displacement of tagging grids between EOI and EOE. Seven different DIR methods were applied to the high-resolution TrueFISP MR images (EOI and EOE) to generate the DIR-based DVFs (dDVF). The DIR methods include Velocity (VEL), MIM, Mirada, multi-grid B-spline from Elastix (MGB) and 3 other algorithms from DIRART toolbox (Double Force Demons (DFD), Improved Lucas-Kanade (ILK), and Iterative Optical Flow (IOF)). All registrations were performed by independent experts. Target registration error (TRE) was calculated as tDVF – dDVF. Analysis was performed for the entire lungs, and separately for the upper and lower lungs. Results: Significant differences between tDVF and dDVF were observed. Besides the DFD and IOF algorithms, all other dDVFs showed similarity in deformation magnitude distribution but away from the ground truth. The average TRE for entire lung ranged 2.5−23.7mm (mean=8.8mm), depending on the DIR method and subject's breathing amplitude. Larger TRE (13.3–23.7mm) was found in subject with larger breathing amplitude of 45.6mm. TRE was greater in lower lung (2.5−33.9 mm, mean=12.4mm) than that in upper lung (2.5−11.9 mm, mean=5.8mm). Conclusion: Significant differences were observed in lung motion estimation between the HP gas tagging MRI method and the DIR methods, especially when lung motion is large. Large variation among different

MO-G-18C-03: Evaluation of Deformable Image Registration for Lung Motion Estimation Using Hyperpolarized Gas Tagging MRI

Energy Technology Data Exchange (ETDEWEB)

Huang, Q; Zhang, Y [Duke University, Durham, NC (United States); Liu, Y [Duke University (United States); Hu, L; Yin, F; Cai, J [Duke University Medical Center, Durham, NC (United States); Miller, W [University of Virginia, Charlottesville, VA (United States)

2014-06-15

Purpose: Hyperpolarized gas (HP) tagging MRI is a novel imaging technique for direct measurement of lung motion during breathing. This study aims to quantitatively evaluate the accuracy of deformable image registration (DIR) in lung motion estimation using HP tagging MRI as references. Methods: Three healthy subjects were imaged using the HP MR tagging, as well as a high-resolution 3D proton MR sequence (TrueFISP) at the end-of-inhalation (EOI) and the end-of-exhalation (EOE). Ground truth of lung motion and corresponding displacement vector field (tDVF) was derived from HP tagging MRI by manually tracking the displacement of tagging grids between EOI and EOE. Seven different DIR methods were applied to the high-resolution TrueFISP MR images (EOI and EOE) to generate the DIR-based DVFs (dDVF). The DIR methods include Velocity (VEL), MIM, Mirada, multi-grid B-spline from Elastix (MGB) and 3 other algorithms from DIRART toolbox (Double Force Demons (DFD), Improved Lucas-Kanade (ILK), and Iterative Optical Flow (IOF)). All registrations were performed by independent experts. Target registration error (TRE) was calculated as tDVF – dDVF. Analysis was performed for the entire lungs, and separately for the upper and lower lungs. Results: Significant differences between tDVF and dDVF were observed. Besides the DFD and IOF algorithms, all other dDVFs showed similarity in deformation magnitude distribution but away from the ground truth. The average TRE for entire lung ranged 2.5−23.7mm (mean=8.8mm), depending on the DIR method and subject's breathing amplitude. Larger TRE (13.3–23.7mm) was found in subject with larger breathing amplitude of 45.6mm. TRE was greater in lower lung (2.5−33.9 mm, mean=12.4mm) than that in upper lung (2.5−11.9 mm, mean=5.8mm). Conclusion: Significant differences were observed in lung motion estimation between the HP gas tagging MRI method and the DIR methods, especially when lung motion is large. Large variation among different

Vision enhanced navigation for unmanned systems

Science.gov (United States)

Wampler, Brandon Loy

A vision based simultaneous localization and mapping (SLAM) algorithm is evaluated for use on unmanned systems. SLAM is a technique used by a vehicle to build a map of an environment while concurrently keeping track of its location within the map, without a priori knowledge. The work in this thesis is focused on using SLAM as a navigation solution when global positioning system (GPS) service is degraded or temporarily unavailable. Previous work on unmanned systems that lead up to the determination that a better navigation solution than GPS alone is first presented. This previous work includes control of unmanned systems, simulation, and unmanned vehicle hardware testing. The proposed SLAM algorithm follows the work originally developed by Davidson et al. in which they dub their algorithm MonoSLAM [1--4]. A new approach using the Pyramidal Lucas-Kanade feature tracking algorithm from Intel's OpenCV (open computer vision) library is presented as a means of keeping correct landmark correspondences as the vehicle moves through the scene. Though this landmark tracking method is unusable for long term SLAM due to its inability to recognize revisited landmarks, as opposed to the Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), its computational efficiency makes it a good candidate for short term navigation between GPS position updates. Additional sensor information is then considered by fusing INS and GPS information into the SLAM filter. The SLAM system, in its vision only and vision/IMU form, is tested on a table top, in an open room, and finally in an outdoor environment. For the outdoor environment, a form of the slam algorithm that fuses vision, IMU, and GPS information is tested. The proposed SLAM algorithm, and its several forms, are implemented in C++ using an Extended Kalman Filter (EKF). Experiments utilizing a live video feed from a webcam are performed. The different forms of the filter are compared and conclusions are made on

Dva nové dokumenty o návštěvě prezidenta Edvarda Beneše ve Spojených státech amerických a Kanadě v květnu a červnu 1943

Czech Academy of Sciences Publication Activity Database

Dejmek, Jindřich

2008-01-01

Roč. 16, - (2008), s. 291-320 ISSN 1210-6860 Institutional research plan: CEZ:AV0Z80150510 Keywords : History of Czechoslovak Foreign Policy * History of Diplomacy * History of International Relations Subject RIV: AB - History

An anti-disturbing real time pose estimation method and system

Science.gov (United States)

Zhou, Jian; Zhang, Xiao-hu

2011-08-01

Pose estimation relating two-dimensional (2D) images to three-dimensional (3D) rigid object need some known features to track. In practice, there are many algorithms which perform this task in high accuracy, but all of these algorithms suffer from features lost. This paper investigated the pose estimation when numbers of known features or even all of them were invisible. Firstly, known features were tracked to calculate pose in the current and the next image. Secondly, some unknown but good features to track were automatically detected in the current and the next image. Thirdly, those unknown features which were on the rigid and could match each other in the two images were retained. Because of the motion characteristic of the rigid object, the 3D information of those unknown features on the rigid could be solved by the rigid object's pose at the two moment and their 2D information in the two images except only two case: the first one was that both camera and object have no relative motion and camera parameter such as focus length, principle point, and etc. have no change at the two moment; the second one was that there was no shared scene or no matched feature in the two image. Finally, because those unknown features at the first time were known now, pose estimation could go on in the followed images in spite of the missing of known features in the beginning by repeating the process mentioned above. The robustness of pose estimation by different features detection algorithms such as Kanade-Lucas-Tomasi (KLT) feature, Scale Invariant Feature Transform (SIFT) and Speed Up Robust Feature (SURF) were compared and the compact of the different relative motion between camera and the rigid object were discussed in this paper. Graphic Processing Unit (GPU) parallel computing was also used to extract and to match hundreds of features for real time pose estimation which was hard to work on Central Processing Unit (CPU). Compared with other pose estimation methods, this new

Evaluation of potential internal target volume of liver tumors using cine-MRI.

Science.gov (United States)

Akino, Yuichi; Oh, Ryoong-Jin; Masai, Norihisa; Shiomi, Hiroya; Inoue, Toshihiko

2014-11-01

Four-dimensional computed tomography (4DCT) is widely used for evaluating moving tumors, including lung and liver cancers. For patients with unstable respiration, however, the 4DCT may not visualize tumor motion properly. High-speed magnetic resonance imaging (MRI) sequences (cine-MRI) permit direct visualization of respiratory motion of liver tumors without considering radiation dose exposure to patients. Here, the authors demonstrated a technique for evaluating internal target volume (ITV) with consideration of respiratory variation using cine-MRI. The authors retrospectively evaluated six patients who received stereotactic body radiotherapy (SBRT) to hepatocellular carcinoma. Before acquiring planning CT, sagittal and coronal cine-MRI images were acquired for 30 s with a frame rate of 2 frames/s. The patient immobilization was conducted under the same condition as SBRT. Planning CT images were then acquired within 15 min from cine-MRI image acquisitions, followed by a 4DCT scan. To calculate tumor motion, the motion vectors between two continuous frames of cine-MRI images were calculated for each frame using the pyramidal Lucas-Kanade method. The target contour was delineated on one frame, and each vertex of the contour was shifted and copied onto the following frame using neighboring motion vectors. 3D trajectory data were generated with the centroid of the contours on sagittal and coronal images. To evaluate the accuracy of the tracking method, the motion of clearly visible blood vessel was analyzed with the motion tracking and manual detection techniques. The target volume delineated on the 50% (end-exhale) phase of 4DCT was translated with the trajectory data, and the distribution of the occupancy probability of target volume was calculated as potential ITV (ITV Potential). The concordance between ITV Potential and ITV estimated with 4DCT (ITV 4DCT) was evaluated using the Dice's similarity coefficient (DSC). The distance between blood vessel positions

Česká emigrace v západní Evropě, USA a Kanadě; národní vědomí a vztah k vlasti v porovnání s postoji Čechů žijících v hranicích národního státu

OpenAIRE

Feitl, David

2016-01-01

The subject of this thesis is a diversified conception of Czechishness. The main proposition is a comparison of types and aspects of relation to the country in the case of (political) emigrants after 1948 in contrast with the "home-based" non-emigrant Czech population. The thesis will briefly mention also the preceding periods of Czech emigration, the socio-economic situation at the turn of the 19th and the 20th centuries, the 1950s etc. All this will be put into the context of the historical...

Evaluation of potential internal target volume of liver tumors using cine-MRI

Energy Technology Data Exchange (ETDEWEB)

Akino, Yuichi, E-mail: akino@radonc.med.osaka-u.ac.jp [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Osaka 5650871, Japan and Miyakojima IGRT Clinic, Miyakojima-ku, Osaka 5340021 (Japan); Oh, Ryoong-Jin; Masai, Norihisa; Shiomi, Hiroya; Inoue, Toshihiko [Miyakojima IGRT Clinic, Miyakojima-ku, Osaka 5340021 (Japan)

2014-11-01

Purpose: Four-dimensional computed tomography (4DCT) is widely used for evaluating moving tumors, including lung and liver cancers. For patients with unstable respiration, however, the 4DCT may not visualize tumor motion properly. High-speed magnetic resonance imaging (MRI) sequences (cine-MRI) permit direct visualization of respiratory motion of liver tumors without considering radiation dose exposure to patients. Here, the authors demonstrated a technique for evaluating internal target volume (ITV) with consideration of respiratory variation using cine-MRI. Methods: The authors retrospectively evaluated six patients who received stereotactic body radiotherapy (SBRT) to hepatocellular carcinoma. Before acquiring planning CT, sagittal and coronal cine-MRI images were acquired for 30 s with a frame rate of 2 frames/s. The patient immobilization was conducted under the same condition as SBRT. Planning CT images were then acquired within 15 min from cine-MRI image acquisitions, followed by a 4DCT scan. To calculate tumor motion, the motion vectors between two continuous frames of cine-MRI images were calculated for each frame using the pyramidal Lucas–Kanade method. The target contour was delineated on one frame, and each vertex of the contour was shifted and copied onto the following frame using neighboring motion vectors. 3D trajectory data were generated with the centroid of the contours on sagittal and coronal images. To evaluate the accuracy of the tracking method, the motion of clearly visible blood vessel was analyzed with the motion tracking and manual detection techniques. The target volume delineated on the 50% (end-exhale) phase of 4DCT was translated with the trajectory data, and the distribution of the occupancy probability of target volume was calculated as potential ITV (ITV {sub Potential}). The concordance between ITV {sub Potential} and ITV estimated with 4DCT (ITV {sub 4DCT}) was evaluated using the Dice’s similarity coefficient (DSC). Results

Islah Çalışmalarından İlgasına Medreselere İslamcı Bir Bakış; Sebilürreşad’da Tevhid-i Tedrisad Kanunu ve Uygulamaları An Islamist View, From The Reforms To The Abolishment Of Medresahs: The Law Of Unification Of Education And Its Practices In Sebilürreşad

Directory of Open Access Journals (Sweden)

Emin ÖZDEMİR

2013-03-01

��Sebilürreşad” magazine. Ders verilen yer anlamına gelen medrese, İslam dünyasının en önemlieğitim-öğretim kurumlarından birisidir. Orta Çağ’da İslammedeniyetinin zirveye ulaşmasında büyük pay sahibi olan bu kurumlar,19. yüzyıldan itibaren İslam dünyasının, Batı karşısında gerilemesininsebebi olarak görülür ve tartışılmaya başlanır. Tanzimat’tan itibarenaçılan Batı tarzı eğitim kurumları karşısında sürekli güç kaybedenmedreselerin ıslahına yönelik, Osmanlı’nın son döneminde gelişendüşünce hareketleri çerçevesinde, farklı çözüm önerileri ortaya konulur.Medreselerin işlevini kaybettiklerini, dolayısıyla kapatılması gerektiğinidüşünen Batıcı aydınların sekülarist kanadına karşın, İslamcı aydınlarüzerinde yapılacak ıslah girişimleriyle bu kurumların çağın şartlarınauygun hale getirilebileceğini belirtirler. Cumhuriyet Türkiye’sinde Batıcıfikirler ekseninde gerçekleştirilen köklü yenilik hareketlerindenmedreseler de etkilenir. Bu kurumlar, Maarif Vekili Vasıf Bey’in Tevhid-iTedrisat Kanunu’na istinaden 11 Mart 1924’te yayınladığı bir genelgeylekapatılır. Medreseler kapatıldıktan sonraki gelişmeler, İslamcıçevrelerde endişe yaratır ve tepkiye yol açar. Bu gelişmelerin bazılarışunlardır; Lağvedilen medreselerde çalışan müderrislerin bir kısmınınişsiz kalması, medrese vakıflarının satılma ya da kiralama yoluylauygunsuz amaçlar için kullanılacağı endişesi, medreselerin yerinekurulan İmam-Hatip Mektepleri ve İlahiyat Fakültelerininmüfredatlarının beklentileri karşılayamaması dolayısıyla din eğitimininakim kalacağı düşüncesidir. Yapmış olduğumuz bu çalışma ilemedreselerin kaldırılması ve bundan mütevellid olumsuz gelişmelere,İslamcı akımın muhalefetini, Sebilürreşad dergisi örneğindeinceleyeceğiz.