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Sample records for robust object tracking

  1. Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking

    Directory of Open Access Journals (Sweden)

    Honghong Yang

    2016-01-01

    Full Text Available Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness.

  2. Robust deformable and occluded object tracking with dynamic graph.

    Science.gov (United States)

    Cai, Zhaowei; Wen, Longyin; Lei, Zhen; Vasconcelos, Nuno; Li, Stan Z

    2014-12-01

    While some efforts have been paid to handle deformation and occlusion in visual tracking, they are still great challenges. In this paper, a dynamic graph-based tracker (DGT) is proposed to address these two challenges in a unified framework. In the dynamic target graph, nodes are the target local parts encoding appearance information, and edges are the interactions between nodes encoding inner geometric structure information. This graph representation provides much more information for tracking in the presence of deformation and occlusion. The target tracking is then formulated as tracking this dynamic undirected graph, which is also a matching problem between the target graph and the candidate graph. The local parts within the candidate graph are separated from the background with Markov random field, and spectral clustering is used to solve the graph matching. The final target state is determined through a weighted voting procedure according to the reliability of part correspondence, and refined with recourse to a foreground/background segmentation. An effective online updating mechanism is proposed to update the model, allowing DGT to robustly adapt to variations of target structure. Experimental results show improved performance over several state-of-the-art trackers, in various challenging scenarios.

  3. Occlusion detection via structured sparse learning for robust object tracking

    KAUST Repository

    Zhang, Tianzhu

    2014-01-01

    Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios, these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object’s track. This is the case when significant occlusion occurs. To accommodate for nonsparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our proposed tracker consistently outperforms the state-of-the-art trackers.

  4. Robust Object Tracking with a Hierarchical Ensemble Framework

    Science.gov (United States)

    2016-10-09

    significant- ly reduce the feature dimensions so that our approach can handle colorful images without suffering from exponential memory explosion; 4...objects can often distract such local patches and lead to drift. Matching mechanism is used to classify candidate regions which are most similar to

  5. Online learning and fusion of orientation appearance models for robust rigid object tracking

    NARCIS (Netherlands)

    Marras, Ioannis; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    2014-01-01

    We introduce a robust framework for learning and fusing of orientation appearance models based on both texture and depth information for rigid object tracking. Our framework fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depth cameras such as the

  6. Online learning and fusion of orientation appearance models for robust rigid object tracking

    NARCIS (Netherlands)

    Marras, Ioannis; Alabort, Joan; Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    We present a robust framework for learning and fusing different modalities for rigid object tracking. Our method fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depths cameras such as the Kinect. To combine these two completely different

  7. Online structured sparse learning with labeled information for robust object tracking

    Science.gov (United States)

    Fan, Baojie; Cong, Yang; Tang, Yandong

    2017-01-01

    We formulate object tracking under the particle filter framework as a collaborative tracking problem. The priori information from training data is exploited effectively to online learn a discriminative and reconstructive dictionary, simultaneously without losing structural information. Specifically, the class label and the semantic structure information are incorporated into the dictionary learning process as the classification error term and ideal coding regularization term, respectively. Combined with the traditional reconstruction error, a unified dictionary learning framework for robust object tracking is constructed. By minimizing the unified objective function with different mixed norm constraints on sparse coefficients, two robust optimizing methods are developed to learn the high-quality dictionary and optimal classifier simultaneously. The best candidate is selected by minimizing the reconstructive error and classification error jointly. As the tracking continues, the proposed algorithms alternate between the robust sparse coding and the dictionary updating. The proposed trackers are empirically compared with 14 state-of-the-art trackers on some challenging video sequences. Both quantitative and qualitative comparisons demonstrate that the proposed algorithms perform well in terms of accuracy and robustness.

  8. Robust Individual-Cell/Object Tracking via PCANet Deep Network in Biomedicine and Computer Vision

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

    2016-01-01

    Full Text Available Tracking individual-cell/object over time is important in understanding drug treatment effects on cancer cells and video surveillance. A fundamental problem of individual-cell/object tracking is to simultaneously address the cell/object appearance variations caused by intrinsic and extrinsic factors. In this paper, inspired by the architecture of deep learning, we propose a robust feature learning method for constructing discriminative appearance models without large-scale pretraining. Specifically, in the initial frames, an unsupervised method is firstly used to learn the abstract feature of a target by exploiting both classic principal component analysis (PCA algorithms with recent deep learning representation architectures. We use learned PCA eigenvectors as filters and develop a novel algorithm to represent a target by composing of a PCA-based filter bank layer, a nonlinear layer, and a patch-based pooling layer, respectively. Then, based on the feature representation, a neural network with one hidden layer is trained in a supervised mode to construct a discriminative appearance model. Finally, to alleviate the tracker drifting problem, a sample update scheme is carefully designed to keep track of the most representative and diverse samples during tracking. We test the proposed tracking method on two standard individual cell/object tracking benchmarks to show our tracker's state-of-the-art performance.

  9. Robust Online Object Tracking Based on Feature Grouping and 2DPCA

    Directory of Open Access Journals (Sweden)

    Ming-Xin Jiang

    2013-01-01

    Full Text Available We present an online object tracking algorithm based on feature grouping and two-dimensional principal component analysis (2DPCA. Firstly, we introduce regularization into the 2DPCA reconstruction and develop an iterative algorithm to represent an object by 2DPCA bases. Secondly, the object templates are grouped into a more discriminative image and a less discriminative image by computing the variance of the pixels in multiple frames. Then, the projection matrix is learned according to the more discriminative image and the less discriminative image, and the samples are projected. The object tracking results are obtained using Bayesian maximum a posteriori probability estimation. Finally, we employ a template update strategy which combines incremental subspace learning and the error matrix to reduce tracking drift. Compared with other popular methods, our method reduces the computational complexity and is very robust to abnormal changes. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm achieves more favorable performance than several state-of-the-art methods.

  10. Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model

    Directory of Open Access Journals (Sweden)

    Changhong Fu

    2016-08-01

    Full Text Available In this paper, we present a novel onboard robust visual algorithm for long-term arbitrary 2D and 3D object tracking using a reliable global-local object model for unmanned aerial vehicle (UAV applications, e.g., autonomous tracking and chasing a moving target. The first main approach in this novel algorithm is the use of a global matching and local tracking approach. In other words, the algorithm initially finds feature correspondences in a way that an improved binary descriptor is developed for global feature matching and an iterative Lucas–Kanade optical flow algorithm is employed for local feature tracking. The second main module is the use of an efficient local geometric filter (LGF, which handles outlier feature correspondences based on a new forward-backward pairwise dissimilarity measure, thereby maintaining pairwise geometric consistency. In the proposed LGF module, a hierarchical agglomerative clustering, i.e., bottom-up aggregation, is applied using an effective single-link method. The third proposed module is a heuristic local outlier factor (to the best of our knowledge, it is utilized for the first time to deal with outlier features in a visual tracking application, which further maximizes the representation of the target object in which we formulate outlier feature detection as a binary classification problem with the output features of the LGF module. Extensive UAV flight experiments show that the proposed visual tracker achieves real-time frame rates of more than thirty-five frames per second on an i7 processor with 640 × 512 image resolution and outperforms the most popular state-of-the-art trackers favorably in terms of robustness, efficiency and accuracy.

  11. Low cost, robust and real time system for detecting and tracking moving objects to automate cargo handling in port terminals

    NARCIS (Netherlands)

    Vaquero, V.; Repiso, E.; Sanfeliu, A.; Vissers, J.; Kwakkernaat, M.

    2016-01-01

    The presented paper addresses the problem of detecting and tracking moving objects for autonomous cargo handling in port terminals using a perception system which input data is a single layer laser scanner. A computationally low cost and robust Detection and Tracking Moving Objects (DATMO) algorithm

  12. Robust object tracking techniques for vision-based 3D motion analysis applications

    Science.gov (United States)

    Knyaz, Vladimir A.; Zheltov, Sergey Y.; Vishnyakov, Boris V.

    2016-04-01

    Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system "Mosca" is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms' evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

  13. Robust 3D Object Tracking from Monocular Images using Stable Parts.

    Science.gov (United States)

    Crivellaro, Alberto; Rad, Mahdi; Verdie, Yannick; Yi, Kwang Moo; Fua, Pascal; Lepetit, Vincent

    2017-05-26

    We present an algorithm for estimating the pose of a rigid object in real-time under challenging conditions. Our method effectively handles poorly textured objects in cluttered, changing environments, even when their appearance is corrupted by large occlusions, and it relies on grayscale images to handle metallic environments on which depth cameras would fail. As a result, our method is suitable for practical Augmented Reality applications including industrial environments. At the core of our approach is a novel representation for the 3D pose of object parts: We predict the 3D pose of each part in the form of the 2D projections of a few control points. The advantages of this representation is three-fold: We can predict the 3D pose of the object even when only one part is visible; when several parts are visible, we can easily combine them to compute a better pose of the object; the 3D pose we obtain is usually very accurate, even when only few parts are visible. We show how to use this representation in a robust 3D tracking framework. In addition to extensive comparisons with the state-of-the-art, we demonstrate our method on a practical Augmented Reality application for maintenance assistance in the ATLAS particle detector at CERN.

  14. Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

    Science.gov (United States)

    Bae, Seung-Hwan; Yoon, Kuk-Jin

    2018-03-01

    Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

  15. Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

    Directory of Open Access Journals (Sweden)

    Mohd Asyraf Zulkifley

    2012-11-01

    Full Text Available In video analytics, robust observation detection is very important as thecontent of the videos varies a lot, especially for tracking implementation. Contraryto the image processing field, the problems of blurring, moderate deformation, lowillumination surroundings, illumination change and homogenous texture are normallyencountered in video analytics. Patch-Based Observation Detection (PBOD is developed toimprove detection robustness to complex scenes by fusing both feature- and template-basedrecognition methods. While we believe that feature-based detectors are more distinctive,however, for finding the matching between the frames are best achieved by a collectionof points as in template-based detectors. Two methods of PBOD—the deterministic andprobabilistic approaches—have been tested to find the best mode of detection. Bothalgorithms start by building comparison vectors at each detected points of interest. Thevectors are matched to build candidate patches based on their respective coordination. Forthe deterministic method, patch matching is done in 2-level test where threshold-basedposition and size smoothing are applied to the patch with the highest correlation value. Forthe second approach, patch matching is done probabilistically by modelling the histogramsof the patches by Poisson distributions for both RGB and HSV colour models. Then,maximum likelihood is applied for position smoothing while a Bayesian approach is appliedfor size smoothing. The result showed that probabilistic PBOD outperforms the deterministicapproach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavyprocessing requirement.

  16. Object tracking with stereo vision

    Science.gov (United States)

    Huber, Eric

    1994-01-01

    A real-time active stereo vision system incorporating gaze control and task directed vision is described. Emphasis is placed on object tracking and object size and shape determination. Techniques include motion-centroid tracking, depth tracking, and contour tracking.

  17. Robust visual tracking with contiguous occlusion constraint

    Science.gov (United States)

    Wang, Pengcheng; Qian, Weixian; Chen, Qian

    2016-02-01

    Visual tracking plays a fundamental role in video surveillance, robot vision and many other computer vision applications. In this paper, a robust visual tracking method that is motivated by the regularized ℓ1 tracker is proposed. We focus on investigating the case that the object target is occluded. Generally, occlusion can be treated as some kind of contiguous outlier with the target object as background. However, the penalty function of the ℓ1 tracker is not robust for relatively dense error distributed in the contiguous regions. Thus, we exploit a nonconvex penalty function and MRFs for outlier modeling, which is more probable to detect the contiguous occluded regions and recover the target appearance. For long-term tracking, a particle filter framework along with a dynamic model update mechanism is developed. Both qualitative and quantitative evaluations demonstrate a robust and precise performance.

  18. Robust video object cosegmentation.

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing; Li, Xuelong; Porikli, Fatih

    2015-10-01

    With ever-increasing volumes of video data, automatic extraction of salient object regions became even more significant for visual analytic solutions. This surge has also opened up opportunities for taking advantage of collective cues encapsulated in multiple videos in a cooperative manner. However, it also brings up major challenges, such as handling of drastic appearance, motion pattern, and pose variations, of foreground objects as well as indiscriminate backgrounds. Here, we present a cosegmentation framework to discover and segment out common object regions across multiple frames and multiple videos in a joint fashion. We incorporate three types of cues, i.e., intraframe saliency, interframe consistency, and across-video similarity into an energy optimization framework that does not make restrictive assumptions on foreground appearance and motion model, and does not require objects to be visible in all frames. We also introduce a spatio-temporal scale-invariant feature transform (SIFT) flow descriptor to integrate across-video correspondence from the conventional SIFT-flow into interframe motion flow from optical flow. This novel spatio-temporal SIFT flow generates reliable estimations of common foregrounds over the entire video data set. Experimental results show that our method outperforms the state-of-the-art on a new extensive data set (ViCoSeg).

  19. Bayesian Tracking of Visual Objects

    Science.gov (United States)

    Zheng, Nanning; Xue, Jianru

    Tracking objects in image sequences involves performing motion analysis at the object level, which is becoming an increasingly important technology in a wide range of computer video applications, including video teleconferencing, security and surveillance, video segmentation, and editing. In this chapter, we focus on sequential Bayesian estimation techniques for visual tracking. We first introduce the sequential Bayesian estimation framework, which acts as the theoretic basis for visual tracking. Then, we present approaches to constructing representation models for specific objects.

  20. Robust online face tracking-by-detection

    NARCIS (Netherlands)

    Comaschi, F.; Stuijk, S.; Basten, T.; Corporaal, H.

    2016-01-01

    The problem of online face tracking from unconstrained videos is still unresolved. Challenges range from coping with severe online appearance variations to coping with occlusion. We propose RFTD (Robust Face Tracking-by-Detection), a system which combines tracking and detection into a single

  1. Robust Tracking Control for Constrained Robots

    OpenAIRE

    Mehdi, Haifa; Boubaker, Olfa

    2014-01-01

    In this paper, a novel robust tracking control law is proposed for constrained robots under unknown stiffness environment. The stability and the robustness of the controller are proved using a Lyapunov-based approach where the relationship between the error dynamics of the robotic system and its energy is investigated. Finally, a 3DOF constrained robotic arm is used to prove the stability, the robustness and the safety of the proposed approach.

  2. ANNOTATION SUPPORTED OCCLUDED OBJECT TRACKING

    Directory of Open Access Journals (Sweden)

    Devinder Kumar

    2012-08-01

    Full Text Available Tracking occluded objects at different depths has become as extremely important component of study for any video sequence having wide applications in object tracking, scene recognition, coding, editing the videos and mosaicking. The paper studies the ability of annotation to track the occluded object based on pyramids with variation in depth further establishing a threshold at which the ability of the system to track the occluded object fails. Image annotation is applied on 3 similar video sequences varying in depth. In the experiment, one bike occludes the other at a depth of 60cm, 80cm and 100cm respectively. Another experiment is performed on tracking humans with similar depth to authenticate the results. The paper also computes the frame by frame error incurred by the system, supported by detailed simulations. This system can be effectively used to analyze the error in motion tracking and further correcting the error leading to flawless tracking. This can be of great interest to computer scientists while designing surveillance systems etc.

  3. Extended Keyframe Detection with Stable Tracking for Multiple 3D Object Tracking.

    Science.gov (United States)

    Youngmin Park; Lepetit, V; Woontack Woo

    2011-11-01

    We present a method that is able to track several 3D objects simultaneously, robustly, and accurately in real time. While many applications need to consider more than one object in practice, the existing methods for single object tracking do not scale well with the number of objects, and a proper way to deal with several objects is required. Our method combines object detection and tracking: frame-to-frame tracking is less computationally demanding but is prone to fail, while detection is more robust but slower. We show how to combine them to take the advantages of the two approaches and demonstrate our method on several real sequences.

  4. Object Tracking by Oversampling Local Features.

    Science.gov (United States)

    Pernici, Federico; Del Bimbo, Alberto

    2014-12-01

    In this paper, we present the ALIEN tracking method that exploits oversampling of local invariant representations to build a robust object/context discriminative classifier. To this end, we use multiple instances of scale invariant local features weakly aligned along the object template. This allows taking into account the 3D shape deviations from planarity and their interactions with shadows, occlusions, and sensor quantization for which no invariant representations can be defined. A non-parametric learning algorithm based on the transitive matching property discriminates the object from the context and prevents improper object template updating during occlusion. We show that our learning rule has asymptotic stability under mild conditions and confirms the drift-free capability of the method in long-term tracking. A real-time implementation of the ALIEN tracker has been evaluated in comparison with the state-of-the-art tracking systems on an extensive set of publicly available video sequences that represent most of the critical conditions occurring in real tracking environments. We have reported superior or equal performance in most of the cases and verified tracking with no drift in very long video sequences.

  5. Tracking in Object Action Space

    DEFF Research Database (Denmark)

    Krüger, Volker; Herzog, Dennis

    2013-01-01

    In this paper we focus on the joint problem of tracking humans and recognizing human action in scenarios such as a kitchen scenario or a scenario where a robot cooperates with a human, e.g., for a manufacturing task. In these scenarios, the human directly interacts with objects physically by using......-dimensional action space. In our approach, we use parametric hidden Markov models to represent parametric movements; particle filtering is used to track in the space of action parameters. We demonstrate its effectiveness on synthetic and on real image sequences using human-upper body single arm actions that involve...

  6. Robust Multitask Multiview Tracking in Videos.

    Science.gov (United States)

    Mei, Xue; Hong, Zhibin; Prokhorov, Danil; Tao, Dacheng

    2015-11-01

    Various sparse-representation-based methods have been proposed to solve tracking problems, and most of them employ least squares (LSs) criteria to learn the sparse representation. In many tracking scenarios, traditional LS-based methods may not perform well owing to the presence of heavy-tailed noise. In this paper, we present a tracking approach using an approximate least absolute deviation (LAD)-based multitask multiview sparse learning method to enjoy robustness of LAD and take advantage of multiple types of visual features, such as intensity, color, and texture. The proposed method is integrated in a particle filter framework, where learning the sparse representation for each view of the single particle is regarded as an individual task. The underlying relationship between tasks across different views and different particles is jointly exploited in a unified robust multitask formulation based on LAD. In addition, to capture the frequently emerging outlier tasks, we decompose the representation matrix to two collaborative components that enable a more robust and accurate approximation. We show that the proposed formulation can be effectively approximated by Nesterov's smoothing method and efficiently solved using the accelerated proximal gradient method. The presented tracker is implemented using four types of features and is tested on numerous synthetic sequences and real-world video sequences, including the CVPR2013 tracking benchmark and ALOV++ data set. Both the qualitative and quantitative results demonstrate the superior performance of the proposed approach compared with several state-of-the-art trackers.

  7. Robust Solar Position Sensor for Tracking Systems

    DEFF Research Database (Denmark)

    Ritchie, Ewen; Argeseanu, Alin; Leban, Krisztina Monika

    2009-01-01

    The paper proposes a new solar position sensor used in tracking system control. The main advantages of the new solution are the robustness and the economical aspect. Positioning accuracy of the tracking system that uses the new sensor is better than 1°. The new sensor uses the ancient principle o...... (bright or dark). In addition, the proposed solar sensor significantly simplifies the operation of the tracking control device.......The paper proposes a new solar position sensor used in tracking system control. The main advantages of the new solution are the robustness and the economical aspect. Positioning accuracy of the tracking system that uses the new sensor is better than 1°. The new sensor uses the ancient principle...... of the solar clock. The sensitive elements are eight ordinary photo-resistors. It is important to note that all the sensors are not selected simultaneously. It is not necessary for sensor operating characteristics to be quasi-identical because the sensor principle is based on extreme operating duty measurement...

  8. Self-paced model learning for robust visual tracking

    Science.gov (United States)

    Huang, Wenhui; Gu, Jason; Ma, Xin; Li, Yibin

    2017-01-01

    In visual tracking, learning a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and the frequency of model updating, which contains many details that could affect the tracking results. Self-paced learning (SPL) has recently been attracting considerable interest in the fields of machine learning and computer vision. SPL is inspired by the learning principle underlying the cognitive process of humans, whose learning process is generally from easier samples to more complex aspects of a task. We propose a tracking method that integrates the learning paradigm of SPL into visual tracking, so reliable samples can be automatically selected for model learning. In contrast to many existing model learning strategies in visual tracking, we discover the missing link between sample selection and model learning, which are combined into a single objective function in our approach. Sample weights and model parameters can be learned by minimizing this single objective function. Additionally, to solve the real-valued learning weight of samples, an error-tolerant self-paced function that considers the characteristics of visual tracking is proposed. We demonstrate the robustness and efficiency of our tracker on a recent tracking benchmark data set with 50 video sequences.

  9. Visual tracking via robust multitask sparse prototypes

    Science.gov (United States)

    Zhang, Huanlong; Hu, Shiqiang; Yu, Junyang

    2015-03-01

    Sparse representation has been applied to an online subspace learning-based tracking problem. To handle partial occlusion effectively, some researchers introduce l1 regularization to principal component analysis (PCA) reconstruction. However, in these traditional tracking methods, the representation of each object observation is often viewed as an individual task so the inter-relationship between PCA basis vectors is ignored. We propose a new online visual tracking algorithm with multitask sparse prototypes, which combines multitask sparse learning with PCA-based subspace representation. We first extend a visual tracking algorithm with sparse prototypes in multitask learning framework to mine inter-relations between subtasks. Then, to avoid the problem that enforcing all subtasks to share the same structure may result in degraded tracking results, we impose group sparse constraints on the coefficients of PCA basis vectors and element-wise sparse constraints on the error coefficients, respectively. Finally, we show that the proposed optimization problem can be effectively solved using the accelerated proximal gradient method with the fast convergence. Experimental results compared with the state-of-the-art tracking methods demonstrate that the proposed algorithm achieves favorable performance when the object undergoes partial occlusion, motion blur, and illumination changes.

  10. LADAR object detection and tracking

    Science.gov (United States)

    Monaco, Sam D.

    2004-10-01

    The paper describes an innovative LADAR system for use in detecting, acquiring and tracking high-speed ballistic such as bullets and mortar shells and rocket propelled objects such as Rocket Propelled Grenades (RPGs) and TOW missiles. This class of targets proves to be a considerable challenge for classical RADAR systems since the target areas are small, velocities are very high and target range is short. The proposed system is based on detector and illuminator technology without any moving parts. The target area is flood illuminated with one or more modulated sources and a proprietary-processing algorithm utilizing phase difference return signals generates target information. All aspects of the system utilize existing, low risk components that are readily available from optical and electronic vendors. Operating the illuminator in a continuously modulated mode permits the target range to be measured by the phase delay of the modulated beam. Target velocity is measured by the Doppler frequency shift of the returned signal.

  11. Robust Feedback Zoom Tracking for Digital Video Surveillance

    Directory of Open Access Journals (Sweden)

    Jin Wang

    2012-06-01

    Full Text Available Zoom tracking is an important function in video surveillance, particularly in traffic management and security monitoring. It involves keeping an object of interest in focus during the zoom operation. Zoom tracking is typically achieved by moving the zoom and focus motors in lenses following the so-called “trace curve”, which shows the in-focus motor positions versus the zoom motor positions for a specific object distance. The main task of a zoom tracking approach is to accurately estimate the trace curve for the specified object. Because a proportional integral derivative (PID controller has historically been considered to be the best controller in the absence of knowledge of the underlying process and its high-quality performance in motor control, in this paper, we propose a novel feedback zoom tracking (FZT approach based on the geometric trace curve estimation and PID feedback controller. The performance of this approach is compared with existing zoom tracking methods in digital video surveillance. The real-time implementation results obtained on an actual digital video platform indicate that the developed FZT approach not only solves the traditional one-to-many mapping problem without pre-training but also improves the robustness for tracking moving or switching objects which is the key challenge in video surveillance.

  12. Robust GPS carrier tracking under ionospheric scintillation

    Science.gov (United States)

    Susi, M.; Andreotti, M.; Aquino, M. H.; Dodson, A.

    2013-12-01

    Small scale irregularities present in the ionosphere can induce fast and unpredictable fluctuations of Radio Frequency (RF) signal phase and amplitude. This phenomenon, known as scintillation, can degrade the performance of a GPS receiver leading to cycle slips, increasing the tracking error and also producing a complete loss of lock. In the most severe scenarios, if the tracking of multiple satellites links is prevented, outages in the GPS service can also occur. In order to render a GPS receiver more robust under scintillation, particular attention should be dedicated to the design of the carrier tracking stage, that is the receiver's part most sensitive to these types of phenomenon. This paper exploits the reconfigurability and flexibility of a GPS software receiver to develop a tracking algorithm that is more robust under ionospheric scintillation. For this purpose, first of all, the scintillation level is monitored in real time. Indeed the carrier phase and the post correlation terms obtained by the PLL (Phase Locked Loop) are used to estimate phi60 and S4 [1], the scintillation indices traditionally used to quantify the level of phase and amplitude scintillations, as well as p and T, the spectral parameters of the fluctuations PSD. The effectiveness of the scintillation parameter computation is confirmed by comparing the values obtained by the software receiver and the ones provided by a commercial scintillation monitoring, i.e. the Septentrio PolarxS receiver [2]. Then the above scintillation parameters and the signal carrier to noise density are exploited to tune the carrier tracking algorithm. In case of very weak signals the FLL (Frequency Locked Loop) scheme is selected in order to maintain the signal lock. Otherwise an adaptive bandwidth Phase Locked Loop (PLL) scheme is adopted. The optimum bandwidth for the specific scintillation scenario is evaluated in real time by exploiting the Conker formula [1] for the tracking jitter estimation. The performance

  13. An object tracking algorithm with embedded gyro information

    Science.gov (United States)

    Zhang, Yutong; Yan, Ding; Yuan, Yating

    2017-01-01

    The high speed attitude maneuver of Unmanned Aerial Vehicle (UAV) always causes large motion between adjacent frames of the video stream produced from the camera fixed on the UAV body, which will severely disrupt the performance of image object tracking process. To solve this problem, this paper proposes a method that using a gyroscope fixed on the camera to measure the angular velocity of camera, and then the object position's substantial change in the video stream is predicted. We accomplished the object tracking based on template matching. Experimental result shows that the object tracking algorithm's performance is improved in its efficiency and robustness with embedded gyroscope information.

  14. Algorithm for dynamic object tracking

    Science.gov (United States)

    Datcu, Mihai P.; Folta, Florin; Toma, Cristian E.

    1992-11-01

    The purpose of this paper is to present a hierarchic processor architecture for the tracking of moving objects. Two goals are envisaged: the definition of a moving window for the target tracking, and multiresolution segmentation needed for scale independent target recognition. Memory windows in single processor systems obtained by software methods are limited in speed for high complexity images. In a multiprocessor system the limitation arises in bus or memory bottleneck. Highly concurrent system architectures have been studied and implemented as crossbar bus systems, multiple buses systems, or hypercube structures. Because of the complexity of these architectures and considering the particularities of image signals we suggest a hierarchic architecture that reduces the number of connections preserving the flexibility and which is well adapted for multiresolution algorithm implementations. The hierarchy is a quadtree. The solution is in using switched bus and block memory partition (granular image memory organization). To organize such an architecture in the first stage, the moving objects are identified in the camera field and the adequate windows are defined. The system is reorganized such as the computing power is concentrated in these windows. Image segmentation and motion prediction are accomplished. Motion parameters are interpreted to adapt the windows and to dynamically reorganize the system. The estimation of the motion parameters is done over low resolution images (top of the pyramid). Multiresolution image representation has been introduced for picture transmission and for scene analysis. The pyramidal implementation was elaborated for the evaluation of the image details at various scales. The multiresolution pyramid is obtained by low pass filtering and subsampling the intermediate result. The technique is applied over a limited range of scale. The multiresolution representations, as a consequence, are close to scale invariance. In the mean time image

  15. Does action disrupt Multiple Object Tracking (MOT?

    Directory of Open Access Journals (Sweden)

    Thornton Ian M.

    2015-01-01

    Full Text Available While the relationship between action and focused attention has been well-studied, less is known about the ability to divide attention while acting. In the current paper we explore this issue using the multiple object tracking (MOT paradigm (Pylyshyn & Storm, 1988. We asked whether planning and executing a display-relevant action during tracking would substantially affect the ability track and later identify targets. In all trials the primary task was to track 4 targets among a set of 8 identical objects. Several times during each trial, one object, selected at random, briefly changed colour. In the baseline MOT trials, these changes were ignored. During active trials, each changed object had to be quickly touched. On a given trial, changed objects were either from the tracking set or were selected at random from all 8 objects. Although there was a small dual-task cost, the need to act did not substantially impair tracking under either touch condition.

  16. Object tracking using active appearance models

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille

    2001-01-01

    This paper demonstrates that (near) real-time object tracking can be accomplished by the deformable template model; the Active Appearance Model (AAM) using only low-cost consumer electronics such as a PC and a web-camera. Successful object tracking of perspective, rotational and translational...

  17. Object tracking with hierarchical multiview learning

    Science.gov (United States)

    Yang, Jun; Zhang, Shunli; Zhang, Li

    2016-09-01

    Building a robust appearance model is useful to improve tracking performance. We propose a hierarchical multiview learning framework to construct the appearance model, which has two layers for tracking. On the top layer, two different views of features, grayscale value and histogram of oriented gradients, are adopted for representation under the cotraining framework. On the bottom layer, for each view of each feature, three different random subspaces are generated to represent the appearance from multiple views. For each random view submodel, the least squares support vector machine is employed to improve the discriminability for concrete and efficient realization. These two layers are combined to construct the final appearance model for tracking. The proposed hierarchical model assembles two types of multiview learning strategies, in which the appearance can be described more accurately and robustly. Experimental results in the benchmark dataset demonstrate that the proposed method can achieve better performance than many existing state-of-the-art algorithms.

  18. Robust Visual Tracking via Exclusive Context Modeling

    KAUST Repository

    Zhang, Tianzhu

    2015-02-09

    In this paper, we formulate particle filter-based object tracking as an exclusive sparse learning problem that exploits contextual information. To achieve this goal, we propose the context-aware exclusive sparse tracker (CEST) to model particle appearances as linear combinations of dictionary templates that are updated dynamically. Learning the representation of each particle is formulated as an exclusive sparse representation problem, where the overall dictionary is composed of multiple {group} dictionaries that can contain contextual information. With context, CEST is less prone to tracker drift. Interestingly, we show that the popular L₁ tracker [1] is a special case of our CEST formulation. The proposed learning problem is efficiently solved using an accelerated proximal gradient method that yields a sequence of closed form updates. To make the tracker much faster, we reduce the number of learning problems to be solved by using the dual problem to quickly and systematically rank and prune particles in each frame. We test our CEST tracker on challenging benchmark sequences that involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that CEST consistently outperforms state-of-the-art trackers.

  19. Robust Tracking with Discriminative Ranking Middle-Level Patches

    Directory of Open Access Journals (Sweden)

    Hong Liu

    2014-04-01

    Full Text Available The appearance model has been shown to be essential for robust visual tracking since it is the basic criterion to locating targets in video sequences. Though existing tracking-by-detection algorithms have shown to be greatly promising, they still suffer from the drift problem, which is caused by updating appearance models. In this paper, we propose a new appearance model composed of ranking middle-level patches to capture more object distinctiveness than traditional tracking-by-detection models. Targets and backgrounds are represented by both low-level bottom-up features and high-level top-down patches, which can compensate each other. Bottom-up features are defined at the pixel level, and each feature gets its discrimination score through selective feature attention mechanism. In top-down feature extraction, rectangular patches are ranked according to their bottom-up discrimination scores, by which all of them are clustered into irregular patches, named ranking middle-level patches. In addition, at the stage of classifier training, the online random forests algorithm is specially refined to reduce drifting problems. Experiments on challenging public datasets and our test videos demonstrate that our approach can effectively prevent the tracker drifting problem and obtain competitive performance in visual tracking.

  20. Robust Tracking Control for a Piezoelectric Actuator

    National Research Council Canada - National Science Library

    Salah, M; McIntyre, M; Dawson, D; Wagner, J

    2006-01-01

    In this paper, a hysteresis model-based nonlinear robust controller is developed for a piezoelectric actuator, utilizing a Lyapunov-based stability analysis, which ensures that a desired displacement...

  1. Group Tracking of Space Objects within Bayesian Framework

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2013-03-01

    Full Text Available It is imperative to efficiently track and catalogue the extensive dense group space objects for space surveillance. As the main instrument for Low Earth Orbit (LEO space surveillance, ground-based radar system is usually limited by its resolving power while tracking the small space debris with high dense population. Thus, the obtained information about target detection and observation will be seriously missed, which makes the traditional tracking method inefficient. Therefore, we conceived the concept of group tracking. The overall motional tendency of the group objects is particularly focused, while the individual object is simultaneously tracked in effect. The tracking procedure is based on the Bayesian frame. According to the restriction among the group center and observations of multi-targets, the reconstruction of targets’ number and estimation of individual trajectory can be greatly improved on the accuracy and robustness in the case of high miss alarm. The Markov Chain Monte Carlo Particle (MCMC-Particle algorism is utilized for solving the Bayesian integral problem. Finally, the simulation of the group space objects tracking is carried out to validate the efficiency of the proposed method.

  2. Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

    Directory of Open Access Journals (Sweden)

    Zhenghao Xi

    2014-01-01

    Full Text Available To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

  3. Deterministic object tracking using Gaussian ringlet and directional edge features

    Science.gov (United States)

    Krieger, Evan W.; Sidike, Paheding; Aspiras, Theus; Asari, Vijayan K.

    2017-10-01

    Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by different pavement or ground types and from changing the sensor or altitude. All of these challenges need to be overcome in order to have a robust object tracker, while attaining a computation time appropriate for real-time processing. To achieve this, we present a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), which employs Kirsch kernel filtering for edge features and a ringlet feature mapping for rotational invariance. The method also includes an automatic scale change component to obtain accurate object boundaries and improvements for lowering computation times. We evaluated the DRIFT algorithm on two challenging WAMI datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Additional evaluations on general tracking video sequences are performed using the Visual Tracker Benchmark and Visual Object Tracking 2014 databases to demonstrate the algorithms ability with additional challenges in long complex sequences including scale change. Experimental results show that the proposed approach yields competitive results compared to state-of-the-art object tracking methods on the testing datasets.

  4. Robust Tracking at the High Luminosity LHC

    CERN Multimedia

    Woods, Natasha Lee

    2018-01-01

    The High Luminosity LHC (HL-LHC) aims to increase the LHC data-set by an order of magnitude in order to increase its potential for discoveries. Starting from the middle of 2026, the HL-LHC is expected to reach the peak instantaneous luminosity of 7.5×10^34cm^-2s^-1 which corresponds to about 200 inelastic proton-proton collisions per beam crossing. To cope with the large radiation doses and high pileup, the current ATLAS Inner Detector will be replaced with a new all-silicon Inner Tracker. In this talk the expected performance of tracking and vertexing with the HL-LHC tracker is presented. Comparison is made to the performance with the Run2 detector. Ongoing developments of the track reconstruction for the HL-LHC are also discussed.

  5. Object tracking on mobile devices using binary descriptors

    Science.gov (United States)

    Savakis, Andreas; Quraishi, Mohammad Faiz; Minnehan, Breton

    2015-03-01

    With the growing ubiquity of mobile devices, advanced applications are relying on computer vision techniques to provide novel experiences for users. Currently, few tracking approaches take into consideration the resource constraints on mobile devices. Designing efficient tracking algorithms and optimizing performance for mobile devices can result in better and more efficient tracking for applications, such as augmented reality. In this paper, we use binary descriptors, including Fast Retina Keypoint (FREAK), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent Features (BRIEF), and Binary Robust Invariant Scalable Keypoints (BRISK) to obtain real time tracking performance on mobile devices. We consider both Google's Android and Apple's iOS operating systems to implement our tracking approach. The Android implementation is done using Android's Native Development Kit (NDK), which gives the performance benefits of using native code as well as access to legacy libraries. The iOS implementation was created using both the native Objective-C and the C++ programing languages. We also introduce simplified versions of the BRIEF and BRISK descriptors that improve processing speed without compromising tracking accuracy.

  6. Integrated audiovisual processing for object localization and tracking

    Science.gov (United States)

    Pingali, Gopal S.

    1997-12-01

    This paper presents a system that combines audio and visual cues for locating and tracking an object, typically a person, in real time. It is shown that combining a speech source localization algorithm with a video-based head tracking algorithm results in a more accurate and robust tracker than that obtained using any one of the audio or visual modalities. Performance evaluation results are presented with a system that runs in real time on a general purpose processor. The multimodal tracker has several applications such as teleconferencing, multimedia kiosks and interactive games.

  7. Space object tracking with delayed measurements

    Science.gov (United States)

    Chen, Huimin; Shen, Dan; Chen, Genshe; Blasch, Erik; Pham, Khanh

    2010-04-01

    This paper is concerned with the nonlinear filtering problem for tracking a space object with possibly delayed measurements. In a distributed dynamic sensing environment, due to limited communication bandwidth and long distances between the earth and the satellites, it is possible for sensor reports to be delayed when the tracking filter receives them. Such delays can be complete (the full observation vector is delayed) or partial (part of the observation vector is delayed), and with deterministic or random time lag. We propose an approximate approach to incorporate delayed measurements without reprocessing the old measurements at the tracking filter. We describe the optimal and suboptimal algorithms for filter update with delayed measurements in an orbital trajectory estimation problem without clutter. Then we extend the work to a single object tracking under clutter where probabilistic data association filter (PDAF) is used to replace the recursive linear minimum means square error (LMMSE) filter and delayed measurements with arbitrary lags are be handled without reprocessing the old measurements. Finally, we demonstrate the proposed algorithms in realistic space object tracking scenarios using the NASA General Mission Analysis Tool (GMAT).

  8. Online object tracking via bag-of-local-patches

    Science.gov (United States)

    Wang, Zhihui; Bo, Chunjuan; Wang, Dong

    2017-01-01

    As one of the most important tasks in computer vision, online object tracking plays a critical role in numerous lines of research, which has drawn a lot of researchers' attention and be of many realistic applications. This paper develops a novel tracking algorithm based on the bag-of-local-patches representation with the discriminative learning scheme. In the first frame, a codebook is learned by applying the Kmeans algorithm to a set of densely sampled local patches of the tracked object, and then used to represent the template and candidate samples. During the tracking process, the similarities between the coding coefficients of the candidates and template are chosen as the likelihood values of these candidates. In addition, we propose effective model updating and discriminative learning schemes to capture the appearance change of the tracked object and incorporate the discriminative information to achieve a robust matching. Both qualitative and quantitative evaluations on some challenging image sequences demonstrate that the proposed tracker performs better than other state-of-the-art tracking methods.

  9. An object detection and tracking system for unmanned surface vehicles

    Science.gov (United States)

    Yang, Jian; Xiao, Yang; Fang, Zhiwen; Zhang, Naiwen; Wang, Li; Li, Tao

    2017-10-01

    Object detection and tracking are critical parts of unmanned surface vehicles(USV) to achieve automatic obstacle avoidance. Off-the-shelf object detection methods have achieved impressive accuracy in public datasets, though they still meet bottlenecks in practice, such as high time consumption and low detection quality. In this paper, we propose a novel system for USV, which is able to locate the object more accurately while being fast and stable simultaneously. Firstly, we employ Faster R-CNN to acquire several initial raw bounding boxes. Secondly, the image is segmented to a few superpixels. For each initial box, the superpixels inside will be grouped into a whole according to a combination strategy, and a new box is thereafter generated as the circumscribed bounding box of the final superpixel. Thirdly, we utilize KCF to track these objects after several frames, Faster-RCNN is again used to re-detect objects inside tracked boxes to prevent tracking failure as well as remove empty boxes. Finally, we utilize Faster R-CNN to detect objects in the next image, and refine object boxes by repeating the second module of our system. The experimental results demonstrate that our system is fast, robust and accurate, which can be applied to USV in practice.

  10. Measures for track complexity and robustness of operation at stations

    DEFF Research Database (Denmark)

    Landex, Alex; Jensen, Lars Wittrup

    2013-01-01

    Stations are often limiting the capacity of a railway network. However, most capacity analysis methods focus on open line capacity. This paper presents methods to analyse and describe stations by the use of complexity and robustness measures at stations.Five methods to analyse infrastructure...... and operation at stations are developed in the paper. The first method is an adapted UIC 406 capacity method that can be used to analyse switch zones and platform tracks at stations with simple track layouts. The second method examines the need for platform tracks and the probability that arriving trains...... will not get a platform track immediately at arrival. The third method is a scalable method that analyses the conflicts and the infrastructure complexity in the switch zone(s). The fourth method can be used to examine the complexity and the expected robustness of timetables at a station. The last method...

  11. An algorithm of adaptive scale object tracking in occlusion

    Science.gov (United States)

    Zhao, Congmei

    2017-05-01

    Although the correlation filter-based trackers achieve the competitive results both on accuracy and robustness, there are still some problems in handling scale variations, object occlusion, fast motions and so on. In this paper, a multi-scale kernel correlation filter algorithm based on random fern detector was proposed. The tracking task was decomposed into the target scale estimation and the translation estimation. At the same time, the Color Names features and HOG features were fused in response level to further improve the overall tracking performance of the algorithm. In addition, an online random fern classifier was trained to re-obtain the target after the target was lost. By comparing with some algorithms such as KCF, DSST, TLD, MIL, CT and CSK, experimental results show that the proposed approach could estimate the object state accurately and handle the object occlusion effectively.

  12. 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.

  13. A combined object-tracking algorithm for omni-directional vision-based AGV navigation

    Science.gov (United States)

    Yuan, Wei; Sun, Jie; Cao, Zuo-Liang; Tian, Jing; Yang, Ming

    2010-03-01

    A combined object-tracking algorithm that realizes the realtime tracking of the selected object through the omni-directional vision with a fisheye lens is presented. The new method combines the modified continuously adaptive mean shift algorithm with the Kalman filter method. With the proposed method, the object-tracking problem when the object reappears after being sheltered completely or moving out of the field of view is solved. The experimental results perform well, and the algorithm proposed here improves the robustness and accuracy of the tracking in the omni-directional vision.

  14. Robust guaranteed cost tracking control of quadrotor UAV with uncertainties.

    Science.gov (United States)

    Xu, Zhiwei; Nian, Xiaohong; Wang, Haibo; Chen, Yinsheng

    2017-07-01

    In this paper, a robust guaranteed cost controller (RGCC) is proposed for quadrotor UAV system with uncertainties to address set-point tracking problem. A sufficient condition of the existence for RGCC is derived by Lyapunov stability theorem. The designed RGCC not only guarantees the whole closed-loop system asymptotically stable but also makes the quadratic performance level built for the closed-loop system have an upper bound irrespective to all admissible parameter uncertainties. Then, an optimal robust guaranteed cost controller is developed to minimize the upper bound of performance level. Simulation results verify the presented control algorithms possess small overshoot and short setting time, with which the quadrotor has ability to perform set-point tracking task well. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism.

    Directory of Open Access Journals (Sweden)

    Bineng Zhong

    Full Text Available To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object, while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object. Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.

  16. Robust Model Predictive Control Schemes for Tracking Setpoints

    Directory of Open Access Journals (Sweden)

    Vu Trieu Minh

    2010-01-01

    Full Text Available This paper briefly reviews the development of nontracking robust model predictive control (RMPC schemes for uncertain systems using linear matrix inequalities (LMIs subject to input saturated and softened state constraints. Then we develop two new tracking setpoint RMPC schemes with common Lyapunov function and with zero terminal equality subject to input saturated and softened state constraints. The novel tracking setpoint RMPC schemes are able to stabilize uncertain systems once the output setpoints lead to the violation of the state constraints. The state violation can be regulated by changing the value of the weighting factor. A brief comparative simulation study of the two tracking setpoint RMPC schemes is done via simple examples to demonstrate the ability of the softened state constraint schemes. Finally, some features of future research from this study are discussed.

  17. EnTracked: Energy-Efficient Robust Position Tracking for Mobile Devices

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun; Jensen, Jakob Langdal; Godsk, Torben

    2009-01-01

    estimate and predict system conditions and mobility. Furthermore they provide evidence for that the system can lower the energy consumption considerably and remain robust when faced with changing system conditions. By validation in several real-world deployments we provide evidence that the real system...... conditions and mobility, schedules position updates to both minimize energy consumption and optimize robustness. The realized system tracks pedestrian targets equipped with GPS-enabled devices. The system is configurable to realize different trade-offs between energy consumption and robustness. We provide......An important feature of a modern mobile device is that it can position itself. Not only for use on the device but also for remote applications that require tracking of the device. To be useful, such position tracking has to be energy-efficient to avoid having a major impact on the battery life...

  18. Tracking Objects with Networked Scattered Directional Sensors

    Directory of Open Access Journals (Sweden)

    P. R. Kumar

    2007-12-01

    Full Text Available We study the problem of object tracking using highly directional sensors—sensors whose field of vision is a line or a line segment. A network of such sensors monitors a certain region of the plane. Sporadically, objects moving in straight lines and at a constant speed cross the region. A sensor detects an object when it crosses its line of sight, and records the time of the detection. No distance or angle measurements are available. The task of the sensors is to estimate the directions and speeds of the objects, and the sensor lines, which are unknown a priori. This estimation problem involves the minimization of a highly nonconvex cost function. To overcome this difficulty, we introduce an algorithm, which we call “adaptive basis algorithm.” This algorithm is divided into three phases: in the first phase, the algorithm is initialized using data from six sensors and four objects; in the second phase, the estimates are updated as data from more sensors and objects are incorporated. The third phase is an optional coordinated transformation. The estimation is done in an “ad-hoc” coordinate system, which we call “adaptive coordinate system.” When more information is available, for example, the location of six sensors, the estimates can be transformed to the “real-world” coordinate system. This constitutes the third phase.

  19. Low-rank sparse learning for robust visual tracking

    KAUST Repository

    Zhang, Tianzhu

    2012-01-01

    In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm capitalizes on the inherent low-rank structure of particle representations that are learned jointly. As such, it casts the tracking problem as a low-rank matrix learning problem. This low-rank sparse tracker (LRST) has a number of attractive properties. (1) Since LRST adaptively updates dictionary templates, it can handle significant changes in appearance due to variations in illumination, pose, scale, etc. (2) The linear representation in LRST explicitly incorporates background templates in the dictionary and a sparse error term, which enables LRST to address the tracking drift problem and to be robust against occlusion respectively. (3) LRST is computationally attractive, since the low-rank learning problem can be efficiently solved as a sequence of closed form update operations, which yield a time complexity that is linear in the number of particles and the template size. We evaluate the performance of LRST by applying it to a set of challenging video sequences and comparing it to 6 popular tracking methods. Our experiments show that by representing particles jointly, LRST not only outperforms the state-of-the-art in tracking accuracy but also significantly improves the time complexity of methods that use a similar sparse linear representation model for particles [1]. © 2012 Springer-Verlag.

  20. Improvement in fast particle track reconstruction with robust statistics

    Science.gov (United States)

    Aartsen, M. G.; Abbasi, R.; Abdou, Y.; Ackermann, M.; Adams, J.; Aguilar, J. A.; Ahlers, M.; Altmann, D.; Auffenberg, J.; Bai, X.; Baker, M.; Barwick, S. W.; Baum, V.; Bay, R.; Beatty, J. J.; Bechet, S.; Becker Tjus, J.; Becker, K.-H.; Benabderrahmane, M. L.; BenZvi, S.; Berghaus, P.; Berley, D.; Bernardini, E.; Bernhard, A.; Besson, D. Z.; Binder, G.; Bindig, D.; Bissok, M.; Blaufuss, E.; Blumenthal, J.; Boersma, D. J.; Bohaichuk, S.; Bohm, C.; Bose, D.; Böser, S.; Botner, O.; Brayeur, L.; Bretz, H.-P.; Brown, A. M.; Bruijn, R.; Brunner, J.; Carson, M.; Casey, J.; Casier, M.; Chirkin, D.; Christov, A.; Christy, B.; Clark, K.; Clevermann, F.; Coenders, S.; Cohen, S.; Cowen, D. F.; Cruz Silva, A. H.; Danninger, M.; Daughhetee, J.; Davis, J. C.; Day, M.; De Clercq, C.; De Ridder, S.; Desiati, P.; de Vries, K. D.; de With, M.; DeYoung, T.; Díaz-Vélez, J. C.; Dunkman, M.; Eagan, R.; Eberhardt, B.; Eisch, J.; Euler, S.; Evenson, P. A.; Fadiran, O.; Fazely, A. R.; Fedynitch, A.; Feintzeig, J.; Feusels, T.; Filimonov, K.; Finley, C.; Fischer-Wasels, T.; Flis, S.; Franckowiak, A.; Frantzen, K.; Fuchs, T.; Gaisser, T. K.; Gallagher, J.; Gerhardt, L.; Gladstone, L.; Glüsenkamp, T.; Goldschmidt, A.; Golup, G.; Gonzalez, J. G.; Goodman, J. A.; Góra, D.; Grandmont, D. T.; Grant, D.; Groß, A.; Ha, C.; Haj Ismail, A.; Hallen, P.; Hallgren, A.; Halzen, F.; Hanson, K.; Heereman, D.; Heinen, D.; Helbing, K.; Hellauer, R.; Hickford, S.; Hill, G. C.; Hoffman, K. D.; Hoffmann, R.; Homeier, A.; Hoshina, K.; Huelsnitz, W.; Hulth, P. O.; Hultqvist, K.; Hussain, S.; Ishihara, A.; Jacobi, E.; Jacobsen, J.; Jagielski, K.; Japaridze, G. S.; Jero, K.; Jlelati, O.; Kaminsky, B.; Kappes, A.; Karg, T.; Karle, A.; Kelley, J. L.; Kiryluk, J.; Kläs, J.; Klein, S. R.; Köhne, J.-H.; Kohnen, G.; Kolanoski, H.; Köpke, L.; Kopper, C.; Kopper, S.; Koskinen, D. J.; Kowalski, M.; Krasberg, M.; Krings, K.; Kroll, G.; Kunnen, J.; Kurahashi, N.; Kuwabara, T.; Labare, M.; Landsman, H.; Larson, M. J.; Lesiak-Bzdak, M.; Leuermann, M.; Leute, J.; Lünemann, J.; Macías, O.; Madsen, J.; Maggi, G.; Maruyama, R.; Mase, K.; Matis, H. S.; McNally, F.; Meagher, K.; Merck, M.; Meures, T.; Miarecki, S.; Middell, E.; Milke, N.; Miller, J.; Mohrmann, L.; Montaruli, T.; Morse, R.; Nahnhauer, R.; Naumann, U.; Niederhausen, H.; Nowicki, S. C.; Nygren, D. R.; Obertacke, A.; Odrowski, S.; Olivas, A.; Omairat, A.; O'Murchadha, A.; Paul, L.; Pepper, J. A.; Pérez de los Heros, C.; Pfendner, C.; Pieloth, D.; Pinat, E.; Posselt, J.; Price, P. B.; Przybylski, G. T.; Rädel, L.; Rameez, M.; Rawlins, K.; Redl, P.; Reimann, R.; Resconi, E.; Rhode, W.; Ribordy, M.; Richman, M.; Riedel, B.; Rodrigues, J. P.; Rott, C.; Ruhe, T.; Ruzybayev, B.; Ryckbosch, D.; Saba, S. M.; Salameh, T.; Sander, H.-G.; Santander, M.; Sarkar, S.; Schatto, K.; Scheriau, F.; Schmidt, T.; Schmitz, M.; Schoenen, S.; Schöneberg, S.; Schönwald, A.; Schukraft, A.; Schulte, L.; Schulz, O.; Seckel, D.; Sestayo, Y.; Seunarine, S.; Shanidze, R.; Sheremata, C.; Smith, M. W. E.; Soldin, D.; Spiczak, G. M.; Spiering, C.; Stamatikos, M.; Stanev, T.; Stasik, A.; Stezelberger, T.; Stokstad, R. G.; Stößl, A.; Strahler, E. A.; Ström, R.; Sullivan, G. W.; Taavola, H.; Taboada, I.; Tamburro, A.; Tepe, A.; Ter-Antonyan, S.; Tešić, G.; Tilav, S.; Toale, P. A.; Toscano, S.; Unger, E.; Usner, M.; Vallecorsa, S.; van Eijndhoven, N.; Van Overloop, A.; van Santen, J.; Vehring, M.; Voge, M.; Vraeghe, M.; Walck, C.; Waldenmaier, T.; Wallraff, M.; Weaver, Ch.; Wellons, M.; Wendt, C.; Westerhoff, S.; Whitehorn, N.; Wiebe, K.; Wiebusch, C. H.; Williams, D. R.; Wissing, H.; Wolf, M.; Wood, T. R.; Woschnagg, K.; Xu, D. L.; Xu, X. W.; Yanez, J. P.; Yodh, G.; Yoshida, S.; Zarzhitsky, P.; Ziemann, J.; Zierke, S.; Zoll, M.; Recht, B.; Ré, C.

    2014-02-01

    The IceCube project has transformed 1 km3 of deep natural Antarctic ice into a Cherenkov detector. Muon neutrinos are detected and their direction is inferred by mapping the light produced by the secondary muon track inside the volume instrumented with photomultipliers. Reconstructing the muon track from the observed light is challenging due to noise, light scattering in the ice medium, and the possibility of simultaneously having multiple muons inside the detector, resulting from the large flux of cosmic ray muons. This paper describes work on two problems: (1) the track reconstruction problem, in which, given a set of observations, the goal is to recover the track of a muon; and (2) the coincident event problem, which is to determine how many muons are active in the detector during a time window. Rather than solving these problems by developing more complex physical models that are applied at later stages of the analysis, our approach is to augment the detector's early reconstruction with data filters and robust statistical techniques. These can be implemented at the level of on-line reconstruction and, therefore, improve all subsequent reconstructions. Using the metric of median angular resolution, a standard metric for track reconstruction, we improve the accuracy in the initial reconstruction direction by 13%. We also present improvements in measuring the number of muons in coincident events: we can accurately determine the number of muons 98% of the time.

  1. Robust pedestrian detection and tracking from a moving vehicle

    Science.gov (United States)

    Tuong, Nguyen Xuan; Müller, Thomas; Knoll, Alois

    2011-01-01

    In this paper, we address the problem of multi-person detection, tracking and distance estimation in a complex scenario using multi-cameras. Specifically, we are interested in a vision system for supporting the driver in avoiding any unwanted collision with the pedestrian. We propose an approach using Histograms of Oriented Gradients (HOG) to detect pedestrians on static images and a particle filter as a robust tracking technique to follow targets from frame to frame. Because the depth map requires expensive computation, we extract depth information of targets using Direct Linear Transformation (DLT) to reconstruct 3D-coordinates of correspondent points found by running Speeded Up Robust Features (SURF) on two input images. Using the particle filter the proposed tracker can efficiently handle target occlusions in a simple background environment. However, to achieve reliable performance in complex scenarios with frequent target occlusions and complex cluttered background, results from the detection module are integrated to create feedback and recover the tracker from tracking failures due to the complexity of the environment and target appearance model variability. The proposed approach is evaluated on different data sets both in a simple background scenario and a cluttered background environment. The result shows that, by integrating detector and tracker, a reliable and stable performance is possible even if occlusion occurs frequently in highly complex environment. A vision-based collision avoidance system for an intelligent car, as a result, can be achieved.

  2. Object Tracking and Designation (OTD). Final report, Phase 2

    Energy Technology Data Exchange (ETDEWEB)

    1990-11-01

    We demonstrated on the Object Tracking and Designation (OTD) project, the effectiveness of the 001 technology to the development of complex scientifically-oriented applications for SDI. This document summarizes the results of the project. In the OTD system, Object sightings from Measurement Processing are sorted by Object Sorting into azimuth/elevation bins, then passed to Object Screening. Object Screening separates sightings which are part of an established track from those for which no track has been established. In Process Sighting, sightings determined to be part of established tracks are sent to Update Tracks; uncorrelated sightings are sent to Generate Tracks. Generate Tracks first performs a rate smoothing of the data in Rate Smoothing. In Candidate Track Selection (CTS) uncorrelated sightings are compared with the previous five to seven frames. Those sightings which can be put together to form a candidate ballistic trajectory are sent to the Trajectory Fitting process. In the Trajectory Fitting process, candidate tracks are fitted to precision trajectories. Valid trajectories are sent to Radiometric Discriminant Initialization in the form of a new track message, and object sightings making up the trajectory are removed from the Object Sighting data structure. In Radiometric Discriminant Initialization, radiometric discriminants are produced from the new track message and the resulting discriminant values used to initialize a track record in the Object Track File data structure which is passed to the Prediction function. The Metric Discrimination process uses angle data to determine object lethality. The object`s designation is then sent to the Prediction process. In the Prediction process the track`s position and uncertainty on the next frame is predicted based upon a coefficient corresponding to the object`s estimated class and on the expected interception of the track and the scanner on the next frame.

  3. Robust Optimal Adaptive Trajectory Tracking Control of Quadrotor Helicopter

    Directory of Open Access Journals (Sweden)

    M. Navabi

    Full Text Available Abstract This paper focuses on robust optimal adaptive control strategy to deal with tracking problem of a quadrotor unmanned aerial vehicle (UAV in presence of parametric uncertainties, actuator amplitude constraints, and unknown time-varying external disturbances. First, Lyapunov-based indirect adaptive controller optimized by particle swarm optimization (PSO is developed for multi-input multi-output (MIMO nonlinear quadrotor to prevent input constraints violation, and then disturbance observer-based control (DOBC technique is aggregated with the control system to attenuate the effects of disturbance generated by an exogenous system. The performance of synthesis control method is evaluated by a new performance index function in time-domain, and the stability analysis is carried out using Lyapunov theory. Finally, illustrative numerical simulations are conducted to demonstrate the effectiveness of the presented approach in altitude and attitude tracking under several conditions, including large time-varying uncertainty, exogenous disturbance, and control input constraints.

  4. Robust feature tracking for endoscopic pose estimation and structure recovery

    Science.gov (United States)

    Speidel, S.; Krappe, S.; Röhl, S.; Bodenstedt, S.; Müller-Stich, B.; Dillmann, R.

    2013-03-01

    Minimally invasive surgery is a highly complex medical discipline with several difficulties for the surgeon. To alleviate these difficulties, augmented reality can be used for intraoperative assistance. For visualization, the endoscope pose must be known which can be acquired with a SLAM (Simultaneous Localization and Mapping) approach using the endoscopic images. In this paper we focus on feature tracking for SLAM in minimally invasive surgery. Robust feature tracking and minimization of false correspondences is crucial for localizing the endoscope. As sensory input we use a stereo endoscope and evaluate different feature types in a developed SLAM framework. The accuracy of the endoscope pose estimation is validated with synthetic and ex vivo data. Furthermore we test the approach with in vivo image sequences from da Vinci interventions.

  5. Robust Output Trajectory Tracking of Car-Like Robot Mobile

    Directory of Open Access Journals (Sweden)

    Aicha Bessas

    2016-06-01

    Full Text Available In this paper, we propose a robust output trajectory tracking based on the differential flatness and the integral sliding mode control of the car-like robot mobile. The trajectory planning and the dynamic linearization are based on the differential flatness property of the robot, whereas the integral sliding mode control is designed to solve the reaching phase problem with the elimination of matched uncertainties and minimization of unmatched one. The effectiveness of the proposed control scheme is demonstrated through simulation studies.

  6. Robust feature tracking on the beating heart for a robotic-guided endoscope.

    Science.gov (United States)

    Elhawary, Haytham; Popovic, Aleksandra

    2011-12-01

    Visualization during minimally invasive bypass surgery on the beating heart can be enhanced by using a robotic-guided endoscope and visual servoing from the endoscopic images. In order to achieve these objectives, this work has focused on developing and testing algorithms for accurate, robust and real-time motion tracking of features on the beating heart, using marker-less approaches and an uncalibrated endoscope. Lucas-Kanade pyramidal optical flow-based algorithms and speeded-up robust features (SURF)-based methods have been extensively evaluated, using a range of developed metrics, in order to quantify accuracy, robustness and drift under a variety of circumstances. Three sets of experiments are reported: the first set compared the two tracking methods, using a beating-heart phantom and a static endoscope; the second set evaluated the methods when images were taken using a moving robotic-guided endoscope; and finally, the Lucas-Kanade optical flow algorithm was extensively tested in a visual servoing application, using a robotic endoscope. The combination of a Lucas-Kanade tracking algorithm and a SURF-based feature detection method gave the best performance in terms of accuracy and robustness of tracking, while preserving real-time computation requirements. The optimal parameters consist of a window size of 51 × 51 pixels and an interframe motion threshold of 20 pixels. Feature tracking was successfully integrated into uncalibrated visual servoing or a robotic-guided endoscope. Robust feature tracking on a beating heart with endoscopic video can be achieved in real-time and may facilitate robotically-assisted, minimally invasive bypass surgery and conventional laparoscopic surgery. Copyright © 2011 John Wiley & Sons, Ltd.

  7. Occlusion Handling in Videos Object Tracking: A Survey

    Science.gov (United States)

    Lee, B. Y.; Liew, L. H.; Cheah, W. S.; Wang, Y. C.

    2014-02-01

    Object tracking in video has been an active research since for decades. This interest is motivated by numerous applications, such as surveillance, human-computer interaction, and sports event monitoring. Many challenges related to tracking objects still remain, this can arise due to abrupt object motion, changing appearance patterns of objects and the scene, non-rigid object structures and most significant are occlusion of tracked object be it object-to-object or object-to-scene occlusions. Generally, occlusion in object tracking occur under three situations: self-occlusion, inter-object occlusion by background scene structure. Self-occlusion occurs most frequently while tracking articulated objects when one part of the object occludes another. Inter-object occlusion occurs when two objects being tracked occlude each other whereas occlusion by the background occurs when a structure in the background occludes the tracked objects. Typically, tracking methods handle occlusion by modelling the object motion using linear and non-linear dynamic models. The derived models will be used to continuously predicting the object location when a tracked object is occluded until the object reappears. Example of these method are Kalman filtering and Particle filtering trackers. Researchers have also utilised other features to resolved occlusion, for example, silhouette projections, colour histogram and optical flow. We will present some result from a previously conducted experiment when tracking single object using Kalman filter, Particle filter and Mean Shift trackers under various occlusion situation in this paper. We will also review various other occlusion handling methods that involved using multiple cameras. In a nutshell, the goal of this paper is to discuss in detail the problem of occlusion in object tracking and review the state of the art occlusion handling methods, classify them into different categories, and identify new trends. Moreover, we discuss the important

  8. Robust maximum power point tracking method for photovoltaic cells

    Energy Technology Data Exchange (ETDEWEB)

    Chu, C.C.; Chen, C.L. [National Cheng Kung Univ., Taiwan (China). Dept. of Aeronautics and Astronautics

    2007-07-01

    This paper described a peak power tracking method that uses a sliding mode control system. The method was designed to track the maximum peak power (MPP) of photovoltaic (PV) applications. The performance of the controller was demonstrated through a series of numerical studies that simulated a PV module designed to deliver a maximum of 60 W of power. An approaching control approach was used to guarantee that system states reached the PV surface and produced MPP consistently. A state space averaging method was used to represent system dynamics. The proposed control law ensured that output voltage remained higher than input voltage. The PV model and proposed approach were modelled and evaluated in relation to robustness to irradiance, temperature, and load. The study demonstrated that the sliding mode approach maintained maximum power output while remaining robust in various external conditions. The system attained steady state irradiance levels within an order of milliseconds. The system was also tested under rapid changes of temperature, where the sliding mode approach was able to maintain output at optimum points. It was concluded that the approach almost reaches the theoretical maximum power of known irradiance and temperature. 20 refs., 1 tab., 9 figs.

  9. Automated Mulitple Object Optical Tracking and Recognition System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — OPTRA proposes to develop an optical tracking system that is capable of recognizing and tracking up to 50 different objects within an approximately 2 degree x 3...

  10. Robust Long-Range Optical Tracking for Tunneling Measurement Tasks

    Science.gov (United States)

    Mossel, Annette; Gerstweiler, Georg; Vonach, Emanuel; Chmelina, Klaus; Kaufmann, Hannes

    2013-04-01

    distances between cameras (baseline) with constraints to a tunnel application scenario, (2) to evaluate robustness of unique target identification and (3) to measure accuracy of estimated 3D position. Our results prove the system's capabilities to continuously track static and moving targets within the whole tracking volume as soon as the target becomes visible to the stereo rig. Thus, preliminary sighting of the target can be omitted. Interferences are filtered and partly occluded targets can be recovered. Up to a distance of 50m with a baseline of 12m, our system provides very high precision of the 3D position estimates with a deviation of 1cm or less along all three spatial axes. At a distance of 70m, our system provides still very high accuracy in the width- and height direction with a deviation of only several millimeters and up to 3cm along the depth axis. These promising results enable our system to act as measurement and monitoring system in rough indoor environments. Furthermore, it can serve as a reliable wide area user tracking system for future mixed reality applications, e.g. for tunnel simulation, training of engineers, machine control, tunnel data interpretation and inspection.

  11. Robust visual multitask tracking via composite sparse model

    Science.gov (United States)

    Jin, Bo; Jing, Zhongliang; Wang, Meng; Pan, Han

    2014-11-01

    Recently, multitask learning was applied to visual tracking by learning sparse particle representations in a joint task, which led to the so-called multitask tracking algorithm (MTT). Although MTT shows impressive tracking performances by mining the interdependencies between particles, the individual feature of each particle is underestimated. The utilized L1,q norm regularization assumes all features are shared between all particles and results in nearly identical representation coefficients in nonsparse rows. We propose a composite sparse multitask tracking algorithm (CSMTT). We develop a composite sparse model to formulate the object appearance as a combination of the shared feature component, the individual feature component, and the outlier component. The composite sparsity is achieved via the L and L1,1 norm minimization, and is optimized by the alternating direction method of multipliers, which provides a favorable reconstruction performance and an impressive computational efficiency. Moreover, a dynamical dictionary updating scheme is proposed to capture appearance changes. CSMTT is tested on real-world video sequences under various challenges, and experimental results show that the composite sparse model achieves noticeable lower reconstruction errors and higher computational speeds than traditional sparse models, and CSMTT has consistently better tracking performances against seven state-of-the-art trackers.

  12. An Object-Oriented Framework for Robust Multivariate Analysis

    Directory of Open Access Journals (Sweden)

    Valentin Todorov

    2009-10-01

    Full Text Available Taking advantage of the S4 class system of the programming environment R, which facilitates the creation and maintenance of reusable and modular components, an object-oriented framework for robust multivariate analysis was developed. The framework resides in the packages robustbase and rrcov and includes an almost complete set of algorithms for computing robust multivariate location and scatter, various robust methods for principal component analysis as well as robust linear and quadratic discriminant analysis. The design of these methods follows common patterns which we call statistical design patterns in analogy to the design patterns widely used in software engineering. The application of the framework to data analysis as well as possible extensions by the development of new methods is demonstrated on examples which themselves are part of the package rrcov.

  13. Robust Dynamic Multi-objective Vehicle Routing Optimization Method.

    Science.gov (United States)

    Guo, Yi-Nan; Cheng, Jian; Luo, Sha; Gong, Dun-Wei

    2017-03-21

    For dynamic multi-objective vehicle routing problems, the waiting time of vehicle, the number of serving vehicles, the total distance of routes were normally considered as the optimization objectives. Except for above objectives, fuel consumption that leads to the environmental pollution and energy consumption was focused on in this paper. Considering the vehicles' load and the driving distance, corresponding carbon emission model was built and set as an optimization objective. Dynamic multi-objective vehicle routing problems with hard time windows and randomly appeared dynamic customers, subsequently, were modeled. In existing planning methods, when the new service demand came up, global vehicle routing optimization method was triggered to find the optimal routes for non-served customers, which was time-consuming. Therefore, robust dynamic multi-objective vehicle routing method with two-phase is proposed. Three highlights of the novel method are: (i) After finding optimal robust virtual routes for all customers by adopting multi-objective particle swarm optimization in the first phase, static vehicle routes for static customers are formed by removing all dynamic customers from robust virtual routes in next phase. (ii)The dynamically appeared customers append to be served according to their service time and the vehicles' statues. Global vehicle routing optimization is triggered only when no suitable locations can be found for dynamic customers. (iii)A metric measuring the algorithms' robustness is given. The statistical results indicated that the routes obtained by the proposed method have better stability and robustness, but may be sub-optimum. Moreover, time-consuming global vehicle routing optimization is avoided as dynamic customers appear.

  14. Feature fusion using ranking for object tracking in aerial imagery

    Science.gov (United States)

    Candemir, Sema; Palaniappan, Kannappan; Bunyak, Filiz; Seetharaman, Guna

    2012-06-01

    due to low quality features or background clutter. Adaptive feature ranking increases the robustness of the tracker in dynamically changing environments especially when the object appearance is changing.

  15. Video Object Tracking in Neural Axons with Fluorescence Microscopy Images

    Directory of Open Access Journals (Sweden)

    Liang Yuan

    2014-01-01

    tracking. In this paper, we describe two automated tracking methods for analyzing neurofilament movement based on two different techniques: constrained particle filtering and tracking-by-detection. First, we introduce the constrained particle filtering approach. In this approach, the orientation and position of a particle are constrained by the axon’s shape such that fewer particles are necessary for tracking neurofilament movement than object tracking techniques based on generic particle filtering. Secondly, a tracking-by-detection approach to neurofilament tracking is presented. For this approach, the axon is decomposed into blocks, and the blocks encompassing the moving neurofilaments are detected by graph labeling using Markov random field. Finally, we compare two tracking methods by performing tracking experiments on real time-lapse image sequences of neurofilament movement, and the experimental results show that both methods demonstrate good performance in comparison with the existing approaches, and the tracking accuracy of the tracing-by-detection approach is slightly better between the two.

  16. Super-resolution imaging applied to moving object tracking

    Science.gov (United States)

    Swalaganata, Galandaru; Ratna Sulistyaningrum, Dwi; Setiyono, Budi

    2017-10-01

    Moving object tracking in a video is a method used to detect and analyze changes that occur in an object that being observed. Visual quality and the precision of the tracked target are highly wished in modern tracking system. The fact that the tracked object does not always seem clear causes the tracking result less precise. The reasons are low quality video, system noise, small object, and other factors. In order to improve the precision of the tracked object especially for small object, we propose a two step solution that integrates a super-resolution technique into tracking approach. First step is super-resolution imaging applied into frame sequences. This step was done by cropping the frame in several frame or all of frame. Second step is tracking the result of super-resolution images. Super-resolution image is a technique to obtain high-resolution images from low-resolution images. In this research single frame super-resolution technique is proposed for tracking approach. Single frame super-resolution was a kind of super-resolution that it has the advantage of fast computation time. The method used for tracking is Camshift. The advantages of Camshift was simple calculation based on HSV color that use its histogram for some condition and color of the object varies. The computational complexity and large memory requirements required for the implementation of super-resolution and tracking were reduced and the precision of the tracked target was good. Experiment showed that integrate a super-resolution imaging into tracking technique can track the object precisely with various background, shape changes of the object, and in a good light conditions.

  17. Object oriented simulation implementation in support of robust system design

    Energy Technology Data Exchange (ETDEWEB)

    1993-04-01

    A very brief description of two ``classes`` developed for use in design optimization and sensitivity analyses are given. These classes are used in simulations of systems in early design phases as well as system response assessments. The instanciated classes were coupled to system models to demonstrate the practically and efficiency of using these objects in complex robust design processes.

  18. Robust Visual Tracking Via Consistent Low-Rank Sparse Learning

    KAUST Repository

    Zhang, Tianzhu

    2014-06-19

    Object tracking is the process of determining the states of a target in consecutive video frames based on properties of motion and appearance consistency. In this paper, we propose a consistent low-rank sparse tracker (CLRST) that builds upon the particle filter framework for tracking. By exploiting temporal consistency, the proposed CLRST algorithm adaptively prunes and selects candidate particles. By using linear sparse combinations of dictionary templates, the proposed method learns the sparse representations of image regions corresponding to candidate particles jointly by exploiting the underlying low-rank constraints. In addition, the proposed CLRST algorithm is computationally attractive since temporal consistency property helps prune particles and the low-rank minimization problem for learning joint sparse representations can be efficiently solved by a sequence of closed form update operations. We evaluate the proposed CLRST algorithm against 14 state-of-the-art tracking methods on a set of 25 challenging image sequences. Experimental results show that the CLRST algorithm performs favorably against state-of-the-art tracking methods in terms of accuracy and execution time.

  19. A Secure and Robust Object-Based Video Authentication System

    Directory of Open Access Journals (Sweden)

    Dajun He

    2004-10-01

    Full Text Available An object-based video authentication system, which combines watermarking, error correction coding (ECC, and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI.

  20. GPS Based Tracking of Mobile Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Torp, Kristian

    2006-01-01

    Denne artikel beskriver hvorledes man med eksisterende teknologi, herunder Global Position System og General Packet Radio Service, effektivt kan tracke mobile objekter som f.eks. køretøjer med en garanteret nøjagtighed. Først beskrives den teknologiske platform. Herefter beskrives tre forskellige...

  1. A hybrid multi-objective imperialist competitive algorithm and Monte Carlo method for robust safety design of a rail vehicle

    Science.gov (United States)

    Nejlaoui, Mohamed; Houidi, Ajmi; Affi, Zouhaier; Romdhane, Lotfi

    2017-10-01

    This paper deals with the robust safety design optimization of a rail vehicle system moving in short radius curved tracks. A combined multi-objective imperialist competitive algorithm and Monte Carlo method is developed and used for the robust multi-objective optimization of the rail vehicle system. This robust optimization of rail vehicle safety considers simultaneously the derailment angle and its standard deviation where the design parameters uncertainties are considered. The obtained results showed that the robust design reduces significantly the sensitivity of the rail vehicle safety to the design parameters uncertainties compared to the determinist one and to the literature results.

  2. Robust infrared target tracking using discriminative and generative approaches

    Science.gov (United States)

    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.

  3. Homography-based grasp tracking for planar objects

    NARCIS (Netherlands)

    Carloni, Raffaella; Recatala, Gabriel; Melchiorri, Claudio; Sanz, Pedro J.; Cervera, Enric

    The visual tracking of grasp points is an essential operation for the execution of an approaching movement of a robot arm to an object: the grasp points are used as features for the definition of the control law. This work describes a strategy for tracking grasps on planar objects based on the use

  4. Robust visual tracking via multi-task sparse learning

    KAUST Repository

    Zhang, Tianzhu

    2012-06-01

    In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in MTT. By employing popular sparsity-inducing p, q mixed norms (p D; 1), we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular L 1 tracker [15] is a special case of our MTT formulation (denoted as the L 11 tracker) when p q 1. The learning problem can be efficiently solved using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, MTT is computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that MTT methods consistently outperform state-of-the-art trackers. © 2012 IEEE.

  5. Robust visual tracking via structured multi-task sparse learning

    KAUST Repository

    Zhang, Tianzhu

    2012-11-09

    In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in Multi-Task Tracking (MTT). By employing popular sparsity-inducing lp,q mixed norms (specifically p∈2,∞ and q=1), we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular L1 tracker (Mei and Ling, IEEE Trans Pattern Anal Mach Intel 33(11):2259-2272, 2011) is a special case of our MTT formulation (denoted as the L11 tracker) when p=q=1. Under the MTT framework, some of the tasks (particle representations) are often more closely related and more likely to share common relevant covariates than other tasks. Therefore, we extend the MTT framework to take into account pairwise structural correlations between particles (e.g. spatial smoothness of representation) and denote the novel framework as S-MTT. The problem of learning the regularized sparse representation in MTT and S-MTT can be solved efficiently using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, S-MTT and MTT are computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that S-MTT is much better than MTT, and both methods consistently outperform state-of-the-art trackers. © 2012 Springer Science+Business Media New York.

  6. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Directory of Open Access Journals (Sweden)

    Lien Kuo-Chin

    2008-01-01

    Full Text Available Abstract Human tracking is a popular research topic in computer vision. However, occlusion problem often complicates the tracking process. This paper presents the so-called multiview-based cooperative tracking of multiple human objects based on the homographic relation between different views. This cooperative tracking applies two hidden Markov processes (tracking and occlusion processes for each target in each view. The tracking process locates the moving target in each view, whereas the occlusion process represents the possible visibility of the specific target in that designated view. Based on the occlusion process, the cooperative tracking process may reallocate tracking resources for different trackers in different views. Experimental results show the efficiency of the proposed method.

  7. Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

    Science.gov (United States)

    Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

    2017-09-12

    In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

  8. Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach

    Science.gov (United States)

    Tian, Yuan; Guan, Tao; Wang, Cheng

    2010-01-01

    To produce a realistic augmentation in Augmented Reality, the correct relative positions of real objects and virtual objects are very important. In this paper, we propose a novel real-time occlusion handling method based on an object tracking approach. Our method is divided into three steps: selection of the occluding object, object tracking and occlusion handling. The user selects the occluding object using an interactive segmentation method. The contour of the selected object is then tracked in the subsequent frames in real-time. In the occlusion handling step, all the pixels on the tracked object are redrawn on the unprocessed augmented image to produce a new synthesized image in which the relative position between the real and virtual object is correct. The proposed method has several advantages. First, it is robust and stable, since it remains effective when the camera is moved through large changes of viewing angles and volumes or when the object and the background have similar colors. Second, it is fast, since the real object can be tracked in real-time. Last, a smoothing technique provides seamless merging between the augmented and virtual object. Several experiments are provided to validate the performance of the proposed method. PMID:22319278

  9. Eye-tracking study of inanimate objects

    Directory of Open Access Journals (Sweden)

    Ković Vanja

    2009-01-01

    Full Text Available Unlike the animate objects, where participants were consistent in their looking patterns, for inanimates it was difficult to identify both consistent areas of fixations and a consistent order of fixations. Furthermore, in comparison to animate objects, in animates received significantly shorter total looking time, shorter longest looks and a smaller number of overall fixations. However, as with animates, looking patterns did not systematically differ between the naming and non-naming conditions. These results suggested that animacy, but not labelling, impacts on looking behavior in this paradigm. In the light of feature-based accounts of semantic memory organization, one could interpret these findings as suggesting that processing of the animate objects is based on the saliency/diagnosticity of their visual features (which is then reflected through participants eye-movements towards those features, whereas processing of the inanimate objects is based more on functional features (which cannot be easily captured by looking behavior in such a paradigm.

  10. IMPLEMENTATION OF OBJECT TRACKING ALGORITHMS ON THE BASIS OF CUDA TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    B. A. Zalesky

    2014-01-01

    Full Text Available A fast version of correlation algorithm to track objects on video-sequences made by a nonstabilized camcorder is presented. The algorithm is based on comparison of local correlations of the object image and regions of video-frames. The algorithm is implemented in programming technology CUDA. Application of CUDA allowed to attain real time execution of the algorithm. To improve its precision and stability, a robust version of the Kalman filter has been incorporated into the flowchart. Tests showed applicability of the algorithm to practical object tracking.

  11. Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

    Science.gov (United States)

    Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

    2013-12-01

    This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

  12. A problem formulation for glideslope tracking in wind shear using advanced robust control techniques

    Science.gov (United States)

    Belcastro, Christine M.; Chang, B.-C.; Fischl, Robert

    1992-01-01

    A formulation of the longitudinal glideslope tracking of a transport-class aircraft in severe wind shear and turbulence for application to robust control system design is presented. Mathematical wind shear models are incorporated into the vehicle mathematical model, and wind turbulence is modeled as an input disturbance signal. For this problem formulation, the horizontal and vertical wind shear gradients are treated as real uncertain parameters that vary over an entire wind shear profile. The primary objective is to examine the formulation of this problem into an appropriate design format for use in m-synthesis control system design.

  13. Fuzzy model based adaptive synchronization of uncertain chaotic systems: Robust tracking control approach

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, Eun-Ju; Hyun, Chang-Ho; Kim, Euntai [ICS Laboratory (B723), Department of Electrical and Electronic Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749 (Korea, Republic of); Park, Mignon [ICS Laboratory (B723), Department of Electrical and Electronic Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749 (Korea, Republic of)], E-mail: mignpark@yonsei.ac.kr

    2009-05-11

    This Letter presents fuzzy model-based robust tracking control for the adaptive synchronization of uncertain chaotic systems. Fuzzy model and adaptive algorithm are employed to present the unknown chaotic systems. H{sup {infinity}} and sliding mode control are combined to construct a robust tracking controller. The incorporated H{sup {infinity}} controller can attenuate the external disturbance and approximation error to any prescribed level. The proposed scheme guarantees that all the variables are bounded and the tracking error is compensated.

  14. Checking the low track lattice girder bridges for robustness

    Directory of Open Access Journals (Sweden)

    Bucur Carmen

    2016-07-01

    Full Text Available When you say about a thing or a being that they are robust, you imagine a complete entity from the point of view of its component parts giving out force and safety. The notion of robustness is associated with a lot of activity domains. Consequently, there are many definitions individualizing the robustness notion depending on the study domain.

  15. On Improving the Energy Efficiency and Robustness of Position Tracking for Mobile Devices

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun

    2010-01-01

    An important feature of a modern mobile device is that it can position itself and support remote position tracking. To be useful, such position tracking has to be energy-efficient to avoid having a major impact on the battery life of the mobile device. Furthermore, tracking has to robustly deliver...

  16. Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

    Directory of Open Access Journals (Sweden)

    Yazhe Tang

    2015-01-01

    Full Text Available This paper presents a novel surveillance system named thermal omnidirectional vision (TOV system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.

  17. OBJECT TRACKING WITH ROTATION-INVARIANT LARGEST DIFFERENCE INDEXED LOCAL TERNARY PATTERN

    Directory of Open Access Journals (Sweden)

    J Shajeena

    2017-02-01

    Full Text Available This paper presents an ideal method for object tracking directly in the compressed domain in video sequences. An enhanced rotation-invariant image operator called Largest Difference Indexed Local Ternary Pattern (LDILTP has been proposed. The Local Ternary Pattern which worked very well in texture classification and face recognition is now extended for rotation invariant object tracking. Histogramming the LTP code makes the descriptor resistant to translation. The histogram intersection is used to find the similarity measure. This method is robust to noise and retain contrast details. The proposed scheme has been verified on various datasets and shows a commendable performance.

  18. Centralized Fusion of Unscented Kalman Filter Based on Huber Robust Method for Nonlinear Moving Target Tracking

    Directory of Open Access Journals (Sweden)

    Jue Huang

    2015-01-01

    Full Text Available We propose a robust method for tracking nonlinear target with the fusion unscented Kalman filter (FUKF. We noticed that when some outliers exist in the measurements of the sensors, they cannot track the target accurately by using the standard Kalman filters. The robust statistics theory is used in this paper to solve this problem. The measurement noise variance which is at the time of the outlier is restructured through minimizing the designed cost function. Then, the standard fusion unscented Kalman filter is used to track the target in order to avoid the bias brought by the linear approximation. Compared to the traditional tracking method and Huber robust method (HFUKF, this method has a more accurate performance and can track the target efficiently while the outliers exist. Last, simulation examples in three different conditions are given and the simulation results show the advantages of the proposed method over the fusion unscented Kalman filter (FUKF and the Huber robust method (HFUKF.

  19. A Robust Color Object Analysis Approach to Efficient Image Retrieval

    Directory of Open Access Journals (Sweden)

    Ruofei Zhang

    2004-06-01

    Full Text Available We describe a novel indexing and retrieval methodology integrating color, texture, and shape information for content-based image retrieval in image databases. This methodology, we call CLEAR, applies unsupervised image segmentation to partition an image into a set of objects. Fuzzy color histogram, fuzzy texture, and fuzzy shape properties of each object are then calculated to be its signature. The fuzzification procedures effectively resolve the recognition uncertainty stemming from color quantization and human perception of colors. At the same time, the fuzzy scheme incorporates segmentation-related uncertainties into the retrieval algorithm. An adaptive and effective measure for the overall similarity between images is developed by integrating properties of all the objects in every image. In an effort to further improve the retrieval efficiency, a secondary clustering technique is developed and employed, which significantly saves query processing time without compromising retrieval precision. A prototypical system of CLEAR, we developed, demonstrated the promising retrieval performance and robustness in color variations and segmentation-related uncertainties for a test database containing 10 000 general-purpose color images, as compared with its peer systems in the literature.

  20. Joint Conditional Random Field Filter for Multi-Object Tracking

    Directory of Open Access Journals (Sweden)

    Luo Ronghua

    2011-03-01

    Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.

  1. Performance evaluation software moving object detection and tracking in videos

    CERN Document Server

    Karasulu, Bahadir

    2013-01-01

    Performance Evaluation Software: Moving Object Detection and Tracking in Videos introduces a software approach for the real-time evaluation and performance comparison of the methods specializing in moving object detection and/or tracking (D&T) in video processing. Digital video content analysis is an important item for multimedia content-based indexing (MCBI), content-based video retrieval (CBVR) and visual surveillance systems. There are some frequently-used generic algorithms for video object D&T in the literature, such as Background Subtraction (BS), Continuously Adaptive Mean-shift (CMS),

  2. Robust control of dielectric elastomer diaphragm actuator for human pulse signal tracking

    Science.gov (United States)

    Ye, Zhihang; Chen, Zheng; Asmatulu, Ramazan; Chan, Hoyin

    2017-08-01

    Human pulse signal tracking is an emerging technology that is needed in traditional Chinese medicine. However, soft actuation with multi-frequency tracking capability is needed for tracking human pulse signal. Dielectric elastomer (DE) is one type of soft actuating that has great potential in human pulse signal tracking. In this paper, a DE diaphragm actuator was designed and fabricated to track human pulse pressure signal. A physics-based and control-oriented model has been developed to capture the dynamic behavior of DE diaphragm actuator. Using the physical model, an H-infinity robust control was designed for the actuator to reject high-frequency sensing noises and disturbances. The robust control was then implemented in real-time to track a multi-frequency signal, which verified the tracking capability and robustness of the control system. In the human pulse signal tracking test, a human pulse signal was measured at the City University of Hong Kong and then was tracked using DE actuator at Wichita State University in the US. Experimental results have verified that the DE actuator with its robust control is capable of tracking human pulse signal.

  3. Active shape model-based real-time tracking of deformable objects

    Science.gov (United States)

    Kim, Sangjin; Kim, Daehee; Shin, Jeongho; Paik, Joonki

    2005-10-01

    Tracking non-rigid objects such as people in video sequences is a daunting task due to computational complexity and unpredictable environment. The analysis and interpretation of video sequence containing moving, deformable objects have been an active research areas including video tracking, computer vision, and pattern recognition. In this paper we propose a robust, model-based, real-time system to cope with background clutter and occlusion. The proposed algorithm consists of following four steps: (i) localization of an object-of-interest by analyzing four directional motions, (ii) region tracker for tracking moving region detected by the motion detector, (iii) update of training sets using the Smart Snake Algorithm (SSA) without preprocessing, (iv) active shape model-based tracking in region information. The major contribution this work lies in the integration for a completed system, which covers from image processing to tracking algorithms. The approach of combining multiple algorithms succeeds in overcoming fundamental limitations of tracking and at the same time realizes real time implementation. Experimental results show that the proposed algorithm can track people under various environment in real-time. The proposed system has potential uses in the area of surveillance, sape analysis, and model-based coding, to name of few.

  4. Articulated object tracking by rendering consistent appearance parts

    OpenAIRE

    Pezzementi, Z.; Voros, Sandrine; Hager, Gregory D.

    2009-01-01

    International audience; We describe a general methodology for tracking 3-dimensional objects in monocular and stereo video that makes use of GPU-accelerated filtering and rendering in combination with machine learning techniques. The method operates on targets consisting of kinematic chains with known geometry. The tracked target is divided into one or more areas of consistent appearance. The appearance of each area is represented by a classifier trained to assign a class-conditional probabil...

  5. Tracking planets and moons: mechanisms of object tracking revealed with a new paradigm.

    Science.gov (United States)

    Tombu, Michael; Seiffert, Adriane E

    2011-04-01

    People can attend to and track multiple moving objects over time. Cognitive theories of this ability emphasize location information and differ on the importance of motion information. Results from several experiments have shown that increasing object speed impairs performance, although speed was confounded with other properties such as proximity of objects to one another. Here, we introduce a new paradigm to study multiple object tracking in which object speed and object proximity were manipulated independently. Like the motion of a planet and moon, each target-distractor pair rotated about both a common local point as well as the center of the screen. Tracking performance was strongly affected by object speed even when proximity was controlled. Additional results suggest that two different mechanisms are used in object tracking--one sensitive to speed and proximity and the other sensitive to the number of distractors. These observations support models of object tracking that include information about object motion and reject models that use location alone.

  6. Head Tracking via Robust Registration in Texture Map Images

    National Research Council Canada - National Science Library

    LaCascia, Marco

    1998-01-01

    .... The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking...

  7. Device-free object tracking using passive tags

    CERN Document Server

    Han, Jinsong; Zhao, Kun; Jiang, Zhiping

    2014-01-01

    This SpringerBrief examines the use of cheap commercial passive RFID tags to achieve accurate device-free object-tracking. It presents a sensitive detector, named Twins, which uses a pair of adjacent passive tags to detect uncooperative targets (such as intruders). Twins leverages a newly observed phenomenon called critical state that is caused by interference among passive tags.The author expands on the previous object tracking methods, which are mostly device-based, and reveals a new interference model and their extensive experiments for validation. A prototype implementation of the Twins-ba

  8. Robust microbubble tracking for super resolution imaging in ultrasound

    DEFF Research Database (Denmark)

    Hansen, Kristoffer B.; Villagómez Hoyos, Carlos Armando; Brasen, Jens Christian

    2016-01-01

    Currently ultrasound resolution is limited by diffraction to approximately half the wavelength of the sound wave employed. In recent years, super resolution imaging techniques have overcome the diffraction limit through the localization and tracking of a sparse set of microbubbles through the vas...

  9. Three-dimensional tracking of objects in holographic imaging

    Science.gov (United States)

    DaneshPanah, Mehdi; Javidi, Bahram

    2007-09-01

    In this paper we overview on a three dimensional imaging and tracking algorithm in order to track biological specimen in sequence of holographic microscopy images. We use a region tracking method based on MAP estimator in a Bayesian framework and we adapt it to 3D holographic data sequences to efficiently track the desired microorganism. In our formulation, the target-background interface is modeled as the isolevel of a level set function which is evolved at each frame via level set update rule. The statistical characteristics of the target microorganism versus the background are exploited to evolve the interface from one frame to another. Using the bivariate Gaussian distribution to model the reconstructed hologram data enables one to take into account the correlation between the amplitude and phase of the reconstructed field to obtain a more accurate solution. Also, the level set surface evolution provides a robust, efficient and numerically stable method which deals automatically with the change in the topology and geometrical deformations that a microorganism may be subject to.

  10. Mapping and tracking of moving objects in dynamic environments

    CSIR Research Space (South Africa)

    Pancham, A

    2012-10-01

    Full Text Available In order for mobile robots to operate in dynamic or real world environments they must be able to localise themselves while building a map of the environment, and detect and track moving objects. This work involves the research and implementation...

  11. Robust output tracking control of a laboratory helicopter for automatic landing

    Science.gov (United States)

    Liu, Hao; Lu, Geng; Zhong, Yisheng

    2014-11-01

    In this paper, robust output tracking control problem of a laboratory helicopter for automatic landing in high seas is investigated. The motion of the helicopter is required to synchronise with that of an oscillating platform, e.g. the deck of a vessel subject to wave-induced motions. A robust linear time-invariant output feedback controller consisting of a nominal controller and a robust compensator is designed. The robust compensator is introduced to restrain the influences of parametric uncertainties, nonlinearities and external disturbances. It is shown that robust stability and robust tracking property can be achieved simultaneously. Experimental results on the laboratory helicopter for automatic landing demonstrate the effectiveness of the designed control approach.

  12. Tracking Object Existence From an Autonomous Patrol Vehicle

    Science.gov (United States)

    Wolf, Michael; Scharenbroich, Lucas

    2011-01-01

    An autonomous vehicle patrols a large region, during which an algorithm receives measurements of detected potential objects within its sensor range. The goal of the algorithm is to track all objects in the region over time. This problem differs from traditional multi-target tracking scenarios because the region of interest is much larger than the sensor range and relies on the movement of the sensor through this region for coverage. The goal is to know whether anything has changed between visits to the same location. In particular, two kinds of alert conditions must be detected: (1) a previously detected object has disappeared and (2) a new object has appeared in a location already checked. For the time an object is within sensor range, the object can be assumed to remain stationary, changing position only between visits. The problem is difficult because the upstream object detection processing is likely to make many errors, resulting in heavy clutter (false positives) and missed detections (false negatives), and because only noisy, bearings-only measurements are available. This work has three main goals: (1) Associate incoming measurements with known objects or mark them as new objects or false positives, as appropriate. For this, a multiple hypothesis tracker was adapted to this scenario. (2) Localize the objects using multiple bearings-only measurements to provide estimates of global position (e.g., latitude and longitude). A nonlinear Kalman filter extension provides these 2D position estimates using the 1D measurements. (3) Calculate the probability that a suspected object truly exists (in the estimated position), and determine whether alert conditions have been triggered (for new objects or disappeared objects). The concept of a probability of existence was created, and a new Bayesian method for updating this probability at each time step was developed. A probabilistic multiple hypothesis approach is chosen because of its superiority in handling the

  13. Tracking Non-stellar Objects on Ground and in Space

    DEFF Research Database (Denmark)

    Riis, Troels; Jørgensen, John Leif

    1999-01-01

    Many space exploration missions require a fast, early and accurate detection of a specific target. E.g. missions to asteroids, x-ray source missions or interplanetary missions.A second generation star tracker may be used for accurate detection of non-stellar objects of interest for such missions...... approximately down to CCD magnitude mv 7.5), the objects thus listed will include galaxies, nebulae, planets, asteroids, comets and artefacts as satellites.The angular resolution in inertial reference coordinates is a few arcseconds, allowing quite accurate tracking of these objects. Furthermore, the objects...... are easily divided into two classes; Stationary (galaxies, nebulae etc.), and moving object (planets, asteroids, satellite etc.).For missions targeting moving objects, detection down to mv 11 is possible without any system impacts, simply by comparing lists of objects with regular intervals, leaving out all...

  14. Kontrol Tracking Fuzzy Berbasis Performa Robust Untuk Quadrotor

    Directory of Open Access Journals (Sweden)

    Dinang Sohendri

    2017-01-01

    Full Text Available Quadrotor merupakan salah satu jenis UAV (Unmanned Aerial Vehicle yang memiliki 4 buah baling-baling atau propeller. Desain kontrol tracking fuzzy Takagi-Sugeno digunakan untuk mengatur tracking Quadrotor mengikuti sinyal referensi dan kontrol state-feedback untuk mengatur kestabilan Quadrotor. Metode kontrol fuzzy Takagi-Sugeno akan memecahkan permasalahan nonlinearitas dari Quadrotor dengan merepresentasikan dinamika sistem nonlinear menjadi beberapa model linear. Model linear ini diperoleh dari linearisasi dibeberapa titik kerja Quadrotor. Berdasarkan model tersebut, aturan kontrol fuzzy T-S disusun dengan konsep Parallel Distributed Compensation (PDC. Performa tracking H∞ dirancang untuk mencari gain kontroler yang paling sesuai untuk mengatasi gangguan pada sistem. Selanjutnya, persoalan diselesakan dengan pendekatan Linear Matrix Inequality (LMI sehingga diperoleh gain kontrol berbasis performa H∞. Hasil simulasi menunjukkan bahwa sistem kontrol hasil desain dapat mengatur gerak Quadrotor sesuai lintasan yang diinginkan dengan Integral Absolut Error 0,1149 pada sumbu X dan 0,0617 pada sumbu Y. Selain itu, ∞-norm dari performa keluaran memiliki tingkat pelemahan kurang dari γ ketika gangguan diberikan.

  15. The Visual Object Tracking VOT2015 Challenge Results

    KAUST Repository

    Kristan, Matej

    2015-12-07

    The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the appendix. Features of the VOT2015 challenge that go beyond its VOT2014 predecessor are: (i) a new VOT2015 dataset twice as large as in VOT2014 with full annotation of targets by rotated bounding boxes and per-frame attribute, (ii) extensions of the VOT2014 evaluation methodology by introduction of a new performance measure. The dataset, the evaluation kit as well as the results are publicly available at the challenge website.

  16. The Visual Object Tracking VOT2016 Challenge Results

    KAUST Repository

    Kristan, Matej

    2016-11-02

    The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).

  17. On Improving the Energy Efficiency and Robustness of Position Tracking for Mobile Devices

    DEFF Research Database (Denmark)

    Kjærgaard, Mikkel Baun

    An important feature of a modern mobile device is that it can position itself and support remote position tracking. To be useful, such position tracking has to be energy-efficient to avoid having a major impact on the battery life of the mobile device. Furthermore, tracking has to robustly deliver...... position updates when faced with changing conditions such as delays and changing positioning conditions. Previous work has established dynamic tracking systems, such as our EnTracked system, as a solution to address these issues. In this paper we propose a responsibility division for position tracking...... into sensor management strategies and position update protocols and combine the sensor management strategy of EnTracked with position update protocols, which enables the system to further reduce the power consumption with up to 268 mW extending the battery life with up to 36\\%. As our evaluation identify...

  18. A FragTrack algorithm enhancement for total occlusion management in visual object tracking

    Science.gov (United States)

    Adamo, F.; Mazzeo, P. L.; Spagnolo, P.; Distante, C.

    2015-05-01

    In recent years, "FragTrack" has become one of the most cited real time algorithms for visual tracking of an object in a video sequence. However, this algorithm fails when the object model is not present in the image or it is completely occluded, and in long term video sequences. In these sequences, the target object appearance is considerably modified during the time and its comparison with the template established at the first frame is hard to compute. In this work we introduce improvements to the original FragTrack: the management of total object occlusions and the update of the object template. Basically, we use a voting map generated by a non-parametric kernel density estimation strategy that allows us to compute a probability distribution for the distances of the histograms between template and object patches. In order to automatically determine whether the target object is present or not in the current frame, an adaptive threshold is introduced. A Bayesian classifier establishes, frame by frame, the presence of template object in the current frame. The template is partially updated at every frame. We tested the algorithm on well-known benchmark sequences, in which the object is always present, and on video sequences showing total occlusion of the target object to demonstrate the effectiveness of the proposed method.

  19. DEEP-SEE: Joint Object Detection, Tracking and Recognition with Application to Visually Impaired Navigational Assistance

    Directory of Open Access Journals (Sweden)

    Ruxandra Tapu

    2017-10-01

    Full Text Available In this paper, we introduce the so-called DEEP-SEE framework that jointly exploits computer vision algorithms and deep convolutional neural networks (CNNs to detect, track and recognize in real time objects encountered during navigation in the outdoor environment. A first feature concerns an object detection technique designed to localize both static and dynamic objects without any a priori knowledge about their position, type or shape. The methodological core of the proposed approach relies on a novel object tracking method based on two convolutional neural networks trained offline. The key principle consists of alternating between tracking using motion information and predicting the object location in time based on visual similarity. The validation of the tracking technique is performed on standard benchmark VOT datasets, and shows that the proposed approach returns state-of-the-art results while minimizing the computational complexity. Then, the DEEP-SEE framework is integrated into a novel assistive device, designed to improve cognition of VI people and to increase their safety when navigating in crowded urban scenes. The validation of our assistive device is performed on a video dataset with 30 elements acquired with the help of VI users. The proposed system shows high accuracy (>90% and robustness (>90% scores regardless on the scene dynamics.

  20. Object tracking by occlusion detection via structured sparse learning

    KAUST Repository

    Zhang, Tianzhu

    2013-06-01

    Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object\\'s track. This is the case when significant occlusion occurs. To accommodate for non-sparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker consistently outperforms the state-of-the-art. © 2013 IEEE.

  1. Real-time moving objects detection and tracking from airborne infrared camera

    Science.gov (United States)

    Zingoni, Andrea; Diani, Marco; Corsini, Giovanni

    2017-10-01

    Detecting and tracking moving objects in real-time from an airborne infrared (IR) camera offers interesting possibilities in video surveillance, remote sensing and computer vision applications, such as monitoring large areas simultaneously, quickly changing the point of view on the scene and pursuing objects of interest. To fully exploit such a potential, versatile solutions are needed, but, in the literature, the majority of them works only under specific conditions about the considered scenario, the characteristics of the moving objects or the aircraft movements. In order to overcome these limitations, we propose a novel approach to the problem, based on the use of a cheap inertial navigation system (INS), mounted on the aircraft. To exploit jointly the information contained in the acquired video sequence and the data provided by the INS, a specific detection and tracking algorithm has been developed. It consists of three main stages performed iteratively on each acquired frame. The detection stage, in which a coarse detection map is computed, using a local statistic both fast to calculate and robust to noise and self-deletion of the targeted objects. The registration stage, in which the position of the detected objects is coherently reported on a common reference frame, by exploiting the INS data. The tracking stage, in which the steady objects are rejected, the moving objects are tracked, and an estimation of their future position is computed, to be used in the subsequent iteration. The algorithm has been tested on a large dataset of simulated IR video sequences, recreating different environments and different movements of the aircraft. Promising results have been obtained, both in terms of detection and false alarm rate, and in terms of accuracy in the estimation of position and velocity of the objects. In addition, for each frame, the detection and tracking map has been generated by the algorithm, before the acquisition of the subsequent frame, proving its

  2. Vision-Based Object Tracking Algorithm With AR. Drone

    Directory of Open Access Journals (Sweden)

    It Nun Thiang

    2015-08-01

    Full Text Available This paper presents a simple and effective vision-based algorithm for autonomous object tracking of a low-cost AR.Drone quadrotor for moving ground and flying targets. The Open-CV is used for computer vision to estimate the position of the object considering the environmental lighting effect. This is also an off-board control as the visual tracking and control process are performed in the laptop with the help of Wi-Fi link. The information obtained from vision algorithm is used to control roll angle and pitch angle of the drone in the case using bottom camera and to control yaw angle and altitude of the drone when the front camera is used as vision sensor. The experimental results from real tests are presented.

  3. Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

    Directory of Open Access Journals (Sweden)

    Bernardin Keni

    2008-01-01

    Full Text Available Abstract Simultaneous tracking of multiple persons in real-world environments is an active research field and several approaches have been proposed, based on a variety of features and algorithms. Recently, there has been a growing interest in organizing systematic evaluations to compare the various techniques. Unfortunately, the lack of common metrics for measuring the performance of multiple object trackers still makes it hard to compare their results. In this work, we introduce two intuitive and general metrics to allow for objective comparison of tracker characteristics, focusing on their precision in estimating object locations, their accuracy in recognizing object configurations and their ability to consistently label objects over time. These metrics have been extensively used in two large-scale international evaluations, the 2006 and 2007 CLEAR evaluations, to measure and compare the performance of multiple object trackers for a wide variety of tracking tasks. Selected performance results are presented and the advantages and drawbacks of the presented metrics are discussed based on the experience gained during the evaluations.

  4. Efficient Tracking, Logging, and Blocking of Accesses to Digital Objects

    Science.gov (United States)

    2015-09-01

    the performer moved the field of digital provenance forward by designing and implementing techniques for following the chain of custody of data in a... chain of custody of data in a virtualized environment. Specifically, we provided an approach for tracking accesses to objects that originate from...automatically record events that are causally related to each other, and to chain sequences of events. Intuitively, events may be causally related if

  5. Comparison of Three Approximate Kinematic Models for Space Object Tracking

    Science.gov (United States)

    2013-07-01

    Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law , no person shall be subject to a...motion of an Earth orbiting SO follows Newton’s law of universal gravitation and is nonlinear in the ECI (Cartesian) Coordinates. The orbit information...Management for Collision Alert in Orbital Object Tracking,” Proc. SPIE 8044, 2011. [22] Wikipedia, “ Kepler Orbit,” URL: http://en.wikipedia.org/wiki

  6. Robust trajectory tracking control of a dual-arm space robot actuated by control moment gyroscopes

    Science.gov (United States)

    Jia, Yinghong; Misra, Arun K.

    2017-08-01

    It is a new design concept to employ control moment gyroscopes (CMGs) as reactionless actuators for space robots. Such actuation has several noticeable advantages such as weak dynamical coupling and low power consumption over traditional joint motor actuation. This paper presents a robust control law for a CMG-actuated space robot in presence of system uncertainties and closed-chain constraints. The control objective is to make the manipulation variables to track the desired trajectories, and reduce the possibility of CMG saturation simultaneously. A reduced-order dynamical equation in terms of independent motion variables is derived using Kane's equations. Desired trajectories of the independent motion variables are derived by minimum-norm trajectory planning algorithm, and an adaptive sliding mode controller with improved adaptation laws is proposed to drive the independent motion variables tracking the desired trajectories. Uniformly ultimate boundedness of the closed loop system is proven using Lyapunov method. The redundancy of the full-order actual control torques is utilized to generate a null torque vector which reduces the possibility of CMG angular momentum saturation while producing no effect on the reduced-order control input. Simulation results demonstrate the effectiveness of the proposed algorithms and the advantage of weak dynamical coupling of the CMG-actuated system.

  7. Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera

    Science.gov (United States)

    Dziri, Aziz; Duranton, Marc; Chapuis, Roland

    2016-07-01

    Multiple-object tracking constitutes a major step in several computer vision applications, such as surveillance, advanced driver assistance systems, and automatic traffic monitoring. Because of the number of cameras used to cover a large area, these applications are constrained by the cost of each node, the power consumption, the robustness of the tracking, the processing time, and the ease of deployment of the system. To meet these challenges, the use of low-power and low-cost embedded vision platforms to achieve reliable tracking becomes essential in networks of cameras. We propose a tracking pipeline that is designed for fixed smart cameras and which can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on a low-cost embedded smart camera composed of a Raspberry-Pi board and a RaspiCam camera. The tracking quality and the processing speed obtained with the proposed pipeline are evaluated on publicly available datasets and compared to the state-of-the-art methods.

  8. Synthetic Jet Actuator-Based Aircraft Tracking Using a Continuous Robust Nonlinear Control Strategy

    Directory of Open Access Journals (Sweden)

    N. Ramos-Pedroza

    2017-01-01

    Full Text Available A robust nonlinear control law that achieves trajectory tracking control for unmanned aerial vehicles (UAVs equipped with synthetic jet actuators (SJAs is presented in this paper. A key challenge in the control design is that the dynamic characteristics of SJAs are nonlinear and contain parametric uncertainty. The challenge resulting from the uncertain SJA actuator parameters is mitigated via innovative algebraic manipulation in the tracking error system derivation along with a robust nonlinear control law employing constant SJA parameter estimates. A key contribution of the paper is a rigorous analysis of the range of SJA actuator parameter uncertainty within which asymptotic UAV trajectory tracking can be achieved. A rigorous stability analysis is carried out to prove semiglobal asymptotic trajectory tracking. Detailed simulation results are included to illustrate the effectiveness of the proposed control law in the presence of wind gusts and varying levels of SJA actuator parameter uncertainty.

  9. Visual Tracking Utilizing Object Concept from Deep Learning Network

    Science.gov (United States)

    Xiao, C.; Yilmaz, A.; Lia, S.

    2017-05-01

    Despite having achieved good performance, visual tracking is still an open area of research, especially when target undergoes serious appearance changes which are not included in the model. So, in this paper, we replace the appearance model by a concept model which is learned from large-scale datasets using a deep learning network. The concept model is a combination of high-level semantic information that is learned from myriads of objects with various appearances. In our tracking method, we generate the target's concept by combining the learned object concepts from classification task. We also demonstrate that the last convolutional feature map can be used to generate a heat map to highlight the possible location of the given target in new frames. Finally, in the proposed tracking framework, we utilize the target image, the search image cropped from the new frame and their heat maps as input into a localization network to find the final target position. Compared to the other state-of-the-art trackers, the proposed method shows the comparable and at times better performance in real-time.

  10. International Space Station Utilization: Tracking Investigations from Objectives to Results

    Science.gov (United States)

    Ruttley, T. M.; Mayo, Susan; Robinson, J. A.

    2011-01-01

    Since the first module was assembled on the International Space Station (ISS), on-orbit investigations have been underway across all scientific disciplines. The facilities dedicated to research on ISS have supported over 1100 investigations from over 900 scientists representing over 60 countries. Relatively few of these investigations are tracked through the traditional NASA grants monitoring process and with ISS National Laboratory use growing, the ISS Program Scientist s Office has been tasked with tracking all ISS investigations from objectives to results. Detailed information regarding each investigation is now collected once, at the first point it is proposed for flight, and is kept in an online database that serves as a single source of information on the core objectives of each investigation. Different fields are used to provide the appropriate level of detail for research planning, astronaut training, and public communications. http://www.nasa.gov/iss-science/. With each successive year, publications of ISS scientific results, which are used to measure success of the research program, have shown steady increases in all scientific research areas on the ISS. Accurately identifying, collecting, and assessing the research results publications is a challenge and a priority for the ISS research program, and we will discuss the approaches that the ISS Program Science Office employs to meet this challenge. We will also address the online resources available to support outreach and communication of ISS research to the public. Keywords: International Space Station, Database, Tracking, Methods

  11. Robust Position Tracking for Electro-Hydraulic Drives Based on Generalized Feedforward Compensation Approach

    DEFF Research Database (Denmark)

    Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.

    2012-01-01

    This paper presents a robust tracking control concept based on accurate feedforward compensation for hydraulic valve-cylinder drives. The proposed feedforward compensator is obtained utilizing a generalized description of the valve flow that takes into account any asymmetry of valves and/or cylin......This paper presents a robust tracking control concept based on accurate feedforward compensation for hydraulic valve-cylinder drives. The proposed feedforward compensator is obtained utilizing a generalized description of the valve flow that takes into account any asymmetry of valves and...

  12. Conditional Random Field (CRF-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning

    Directory of Open Access Journals (Sweden)

    Ehwa Yang

    2017-03-01

    Full Text Available Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT. In particular, online MOT is more demanding due to its diverse applications in time-critical situations. A main issue of realizing online MOT is how to associate noisy object detection results on a new frame with previously being tracked objects. In this work, we propose a multi-object tracker method called CRF-boosting which utilizes a hybrid data association method based on online hybrid boosting facilitated by a conditional random field (CRF for establishing online MOT. For data association, learned CRF is used to generate reliable low-level tracklets and then these are used as the input of the hybrid boosting. To do so, while existing data association methods based on boosting algorithms have the necessity of training data having ground truth information to improve robustness, CRF-boosting ensures sufficient robustness without such information due to the synergetic cascaded learning procedure. Further, a hierarchical feature association framework is adopted to further improve MOT accuracy. From experimental results on public datasets, we could conclude that the benefit of proposed hybrid approach compared to the other competitive MOT systems is noticeable.

  13. Robust watermarking of video objects for MPEG-4 applications

    Science.gov (United States)

    Bas, Patrick; Boulgouris, Nikolaos V.; Koravos, Filippos D.; Chassery, Jean-Marc; Strintzis, Michael G.; Macq, Benoit M. M.

    2001-12-01

    This paper presents two different watermarking schemes devoted to protect video objects. The first presented scheme performs embedding and detection in the uncompressed domain. It has been developed to enable signature detection after object manipulations such as rotations, translations and VOL modifications. To achieve these requirements, the first scheme exploits the shape of the object using CPA analysis: a random sequence is transformed to fit the scale and the orientation of the object. The detection of the mark is performed applying an inverse transform and calculating a correlation between the random sequence and the transformed object. The second scheme is based on compressed-domain processing of video objects. Two different signals are embedded, one for synchronization recovery and another for copyright protection. Both signals are embedded and detected in the compressed domain. During detection, first synchronization recovery is performed and then the copyright watermark is extracted.

  14. Visual Tracking of Deformation and Classification of Non-Rigid Objects with Robot Hand Probing

    Directory of Open Access Journals (Sweden)

    Fei Hui

    2017-03-01

    Full Text Available Performing tasks with a robot hand often requires a complete knowledge of the manipulated object, including its properties (shape, rigidity, surface texture and its location in the environment, in order to ensure safe and efficient manipulation. While well-established procedures exist for the manipulation of rigid objects, as well as several approaches for the manipulation of linear or planar deformable objects such as ropes or fabric, research addressing the characterization of deformable objects occupying a volume remains relatively limited. The paper proposes an approach for tracking the deformation of non-rigid objects under robot hand manipulation using RGB-D data. The purpose is to automatically classify deformable objects as rigid, elastic, plastic, or elasto-plastic, based on the material they are made of, and to support recognition of the category of such objects through a robotic probing process in order to enhance manipulation capabilities. The proposed approach combines advantageously classical color and depth image processing techniques and proposes a novel combination of the fast level set method with a log-polar mapping of the visual data to robustly detect and track the contour of a deformable object in a RGB-D data stream. Dynamic time warping is employed to characterize the object properties independently from the varying length of the tracked contour as the object deforms. The proposed solution achieves a classification rate over all categories of material of up to 98.3%. When integrated in the control loop of a robot hand, it can contribute to ensure stable grasp, and safe manipulation capability that will preserve the physical integrity of the object.

  15. A non-disruptive technology for robust 3D tool tracking for ultrasound-guided interventions.

    Science.gov (United States)

    Mung, Jay; Vignon, Francois; Jain, Ameet

    2011-01-01

    In the past decade ultrasound (US) has become the preferred modality for a number of interventional procedures, offering excellent soft tissue visualization. The main limitation however is limited visualization of surgical tools. A new method is proposed for robust 3D tracking and US image enhancement of surgical tools under US guidance. Small US sensors are mounted on existing surgical tools. As the imager emits acoustic energy, the electrical signal from the sensor is analyzed to reconstruct its 3D coordinates. These coordinates can then be used for 3D surgical navigation, similar to current day tracking systems. A system with real-time 3D tool tracking and image enhancement was implemented on a commercial ultrasound scanner and 3D probe. Extensive water tank experiments with a tracked 0.2mm sensor show robust performance in a wide range of imaging conditions and tool position/orientations. The 3D tracking accuracy was 0.36 +/- 0.16mm throughout the imaging volume of 55 degrees x 27 degrees x 150mm. Additionally, the tool was successfully tracked inside a beating heart phantom. This paper proposes an image enhancement and tool tracking technology with sub-mm accuracy for US-guided interventions. The technology is non-disruptive, both in terms of existing clinical workflow and commercial considerations, showing promise for large scale clinical impact.

  16. Finite-Time Control for Robust Tracking Consensus in MASs With an Uncertain Leader.

    Science.gov (United States)

    Lu, Xiaoqing; Wang, Yaonan; Yu, Xinghuo; Lai, Jingang

    2017-05-01

    This paper investigates the finite-time control for robust tracking consensus problems of multiagent systems with an uncertain leader for situations where the state of the considered active leader may not be measured and the directed network topology is time-varying. Based on the neighbor-based state-estimation rule and a new Lyapunov stability analysis method, a continuous and nonlinear distributed tracking protocol using only relative position information is designed, under which each agent can follow the leader in finite time if the input (acceleration) of the leader is known, and the tracking errors can converge to a bounded region in finite time if the input of the leader is unknown. In particular, a special continuous distributed tracking protocol with bounded control inputs is introduced to track the active leader in finite time. Numerical simulations are also given to illustrate the effectiveness of the theoretic results.

  17. Robust B+ -Tree-Based Indexing of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Tiesyte, Dalia; Tradisauskas, Nerius

    2006-01-01

    With the emergence of an infrastructure that enables the geo-positioning of on-line, mobile users, the management of so-called moving objects has emerged as an active area of research. Among the indexing techniques for efficiently answering predictive queries on moving-object positions, the recen...... predecessor?it significantly reduces the number of I/O operations per query for the workloads considered. In many settings, the TPR-tree is outperformed as well....

  18. Patch Based Multiple Instance Learning Algorithm for Object Tracking.

    Science.gov (United States)

    Wang, Zhenjie; Wang, Lijia; Zhang, Hua

    2017-01-01

    To deal with the problems of illumination changes or pose variations and serious partial occlusion, patch based multiple instance learning (P-MIL) algorithm is proposed. The algorithm divides an object into many blocks. Then, the online MIL algorithm is applied on each block for obtaining strong classifier. The algorithm takes account of both the average classification score and classification scores of all the blocks for detecting the object. In particular, compared with the whole object based MIL algorithm, the P-MIL algorithm detects the object according to the unoccluded patches when partial occlusion occurs. After detecting the object, the learning rates for updating weak classifiers' parameters are adaptively tuned. The classifier updating strategy avoids overupdating and underupdating the parameters. Finally, the proposed method is compared with other state-of-the-art algorithms on several classical videos. The experiment results illustrate that the proposed method performs well especially in case of illumination changes or pose variations and partial occlusion. Moreover, the algorithm realizes real-time object tracking.

  19. Robust object recognition based on HMAX model architecture

    Science.gov (United States)

    Chang, Yongxin; Xu, Zhiyong; Zhang, Jing; Fu, Chengyu; Gao, Chunming

    2012-11-01

    In this paper, we describe in detail the hierarchical model and X (HMAX) model of Riesenhuber and Poggio. The HMAX model, accounting for visual processing and making plausible predictions founded on prior information, is built up by alternating simple cell layers and complex cell layers. We generalize the principal facts about the ventral visual stream and argue hierarchy of brain areas to mediate object recognition in visual cortex. Then, in order to obtain the futures of object, we implement Gabor filters and alternately apply template matching and maximum operations for input image. Finally according to the target feature saliency and position information, we introduce a novel algorithm for object recognition in clutter based on the HMAX architecture. The improved model is competitive with current recognizing algorithms on standard database, such as the UICI car and the Caltech101 database including a large number of diverse categories. We also prove that the approach combining spatial position information of parts with the feature fusing can further promotes the recognition rate. The experimental results demonstrate that the proposed approach can recognize objects more precisely and the performance outperforms the standard model.

  20. Tracking hidden objects with a single-photon camera

    CERN Document Server

    Gariepy, Genevieve; Henderson, Robert; Leach, Jonathan; Faccio, Daniele

    2015-01-01

    The ability to know what is hidden around a corner or behind a wall provides a crucial advantage when physically going around the obstacle is impossible or dangerous. Previous solutions to this challenge were constrained e.g. by their physical size, the requirement of reflective surfaces or long data acquisition times. These impede both the deployment of the technology outside the laboratory and the development of significant advances, such as tracking the movement of large-scale hidden objects. We demonstrate a non-line-of-sight laser ranging technology that relies upon the ability, using only a floor surface, to send and detect light that is scattered around an obstacle. A single-photon avalanche diode (SPAD) camera detects light back-scattered from a hidden object that can then be located with centimetre precision, simultaneously tracking its movement. This non-line-of-sight laser ranging system is also shown to work at human length scales, paving the way for a variety of real-life situations.

  1. Multivariable Super Twisting Based Robust Trajectory Tracking Control for Small Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Xing Fang

    2015-01-01

    Full Text Available This paper presents a highly robust trajectory tracking controller for small unmanned helicopter with model uncertainties and external disturbances. First, a simplified dynamic model is developed, where the model uncertainties and external disturbances are treated as compounded disturbances. Then the system is divided into three interconnected subsystems: altitude subsystem, yaw subsystem, and horizontal subsystem. Second, a disturbance observer based controller (DOBC is designed based upon backstepping and multivariable super twisting control algorithm to obtain robust trajectory tracking property. A sliding mode observer works as an estimator of the compounded disturbances. In order to lessen calculative burden, a first-order exact differentiator is employed to estimate the time derivative of the virtual control. Moreover, proof of the stability of the closed-loop system based on Lyapunov method is given. Finally, simulation results are presented to illustrate the effectiveness and robustness of the proposed flight control scheme.

  2. Learning to Detect Objects from Eye-Tracking Data

    Directory of Open Access Journals (Sweden)

    D.P Papadopoulous

    2014-08-01

    Full Text Available One of the bottlenecks in computer vision, especially in object detection, is the need for a large amount of training data. Typically, this is acquired by manually annotating images by hand. In this study, we explore the possibility of using eye-trackers to provide training data for supervised machine learning. We have created a new large scale eye-tracking dataset, collecting fixation data for 6270 images from the Pascal VOC 2012 database. This represents 10 of the 20 classes included in the Pascal database. Each image was viewed by 5 observers, and a total of over 178k fixations have been collected. While previous attempts at using fixation data in computer vision were based on a free-viewing paradigm, we used a visual search task in order to increase the proportion of fixations on the target object. Furthermore, we divided the dataset into five pairs of semantically similar classes (cat/dog, bicycle/motorbike, horse/cow, boat/aeroplane and sofa/diningtable, with the observer having to decide which class each image belonged to. This kept the observer's task simple, while decreasing the chance of them using the scene gist to identify the target parafoveally. In order to alleviate the central bias in scene viewing, the images were presented to the observers with a random offset. The goal of our project is to use the eye-tracking information in order to detect and localise the attended objects. Our model so far, based on features representing the location of the fixations and an appearance model of the attended regions, can successfully predict the location of the target objects in over half of images.

  3. Robust Object Recognition under Partial Occlusions Using NMF

    Directory of Open Access Journals (Sweden)

    Daniel Soukup

    2008-01-01

    Full Text Available In recent years, nonnegative matrix factorization (NMF methods of a reduced image data representation attracted the attention of computer vision community. These methods are considered as a convenient part-based representation of image data for recognition tasks with occluded objects. A novel modification in NMF recognition tasks is proposed which utilizes the matrix sparseness control introduced by Hoyer. We have analyzed the influence of sparseness on recognition rates (RRs for various dimensions of subspaces generated for two image databases, ORL face database, and USPS handwritten digit database. We have studied the behavior of four types of distances between a projected unknown image object and feature vectors in NMF subspaces generated for training data. One of these metrics also is a novelty we proposed. In the recognition phase, partial occlusions in the test images have been modeled by putting two randomly large, randomly positioned black rectangles into each test image.

  4. Hybrid Robust Multi-Objective Evolutionary Optimization Algorithm

    Science.gov (United States)

    2009-03-10

    Algorithm ( MOHO ) with Automatic Switching 4 Two-Objective Hybrid Optimization with a Response Surface 12 Response Surfaces using Wavelet-Based Neural...optimization. Results presented in this report confirm that MOHO is one such optimization concept that works. Multi-dimensional response surfaces... MOHO ) With Automatic Switching Among Individual Search Algorithms The MOHO software [1,2,3] that was developed as a part of this effort is a high

  5. Robust motion tracking in liver from 2D ultrasound images using supporters.

    Science.gov (United States)

    Ozkan, Ece; Tanner, Christine; Kastelic, Matej; Mattausch, Oliver; Makhinya, Maxim; Goksel, Orcun

    2017-06-01

    Effectiveness of image-guided radiation therapy with precise dose delivery depends highly on accurate target localization, which may involve motion during treatment due to, e.g., breathing and drift. Therefore, it is important to track the motion and adjust the radiation delivery accordingly. Tracking generally requires reliable target appearance and image features, whereas in ultrasound imaging acoustic shadowing and other artifacts may degrade the visibility of a target, leading to substantial tracking errors. To minimize such errors, we propose a method based on so-called supporters, a computer vision tracking technique. This allows us to leverage information from surrounding motion for improving robustness of motion tracking on 2D ultrasound image sequences of the liver. Image features, potentially useful for predicting the target positions, are individually tracked, and a supporter model capturing the coupling of motion between these features and the target is learned on-line. This model is then applied to predict the target position, when the target cannot be otherwise tracked reliably. The proposed method was evaluated using the Challenge on Liver Ultrasound Tracking (CLUST)-2015 dataset. Leave-one-out cross-validation was performed on the training set of 24 2D image sequences of each 1-5 min. The method was then applied on the test set (24 2D sequences), where the results were evaluated by the challenge organizers, yielding 1.04 mm mean and 2.26 mm 95%ile tracking error for all targets. We also devised a simulation framework to emulate acoustic shadowing artifacts from the ribs, which showed effective tracking despite the shadows. Results support the feasibility and demonstrate the advantages of using supporters. The proposed method improves its baseline tracker, which uses optic flow and elliptic vessel models, and yields the state-of-the-art real-time tracking solution for the CLUST challenge.

  6. Using Many-Objective Optimization and Robust Decision Making to Identify Robust Regional Water Resource System Plans

    Science.gov (United States)

    Matrosov, E. S.; Huskova, I.; Harou, J. J.

    2015-12-01

    Water resource system planning regulations are increasingly requiring potential plans to be robust, i.e., perform well over a wide range of possible future conditions. Robust Decision Making (RDM) has shown success in aiding the development of robust plans under conditions of 'deep' uncertainty. Under RDM, decision makers iteratively improve the robustness of a candidate plan (or plans) by quantifying its vulnerabilities to future uncertain inputs and proposing ameliorations. RDM requires planners to have an initial candidate plan. However, if the initial plan is far from robust, it may take several iterations before planners are satisfied with its performance across the wide range of conditions. Identifying an initial candidate plan is further complicated if many possible alternative plans exist and if performance is assessed against multiple conflicting criteria. Planners may benefit from considering a plan that already balances multiple performance criteria and provides some level of robustness before the first RDM iteration. In this study we use many-objective evolutionary optimization to identify promising plans before undertaking RDM. This is done for a very large regional planning problem spanning the service area of four major water utilities in East England. The five-objective optimization is performed under an ensemble of twelve uncertainty scenarios to ensure the Pareto-approximate plans exhibit an initial level of robustness. New supply interventions include two reservoirs, one aquifer recharge and recovery scheme, two transfers from an existing reservoir, five reuse and five desalination schemes. Each option can potentially supply multiple demands at varying capacities resulting in 38 unique decisions. Four candidate portfolios were selected using trade-off visualization with the involved utilities. The performance of these plans was compared under a wider range of possible scenarios. The most balanced plan was then submitted into the vulnerability

  7. A Robust Inner and Outer Loop Control Method for Trajectory Tracking of a Quadrotor

    Science.gov (United States)

    Xia, Dunzhu; Cheng, Limei; Yao, Yanhong

    2017-01-01

    In order to achieve the complicated trajectory tracking of quadrotor, a geometric inner and outer loop control scheme is presented. The outer loop generates the desired rotation matrix for the inner loop. To improve the response speed and robustness, a geometric SMC controller is designed for the inner loop. The outer loop is also designed via sliding mode control (SMC). By Lyapunov theory and cascade theory, the closed-loop system stability is guaranteed. Next, the tracking performance is validated by tracking three representative trajectories. Then, the robustness of the proposed control method is illustrated by trajectory tracking in presence of model uncertainty and disturbances. Subsequently, experiments are carried out to verify the method. In the experiment, ultra wideband (UWB) is used for indoor positioning. Extended Kalman Filter (EKF) is used for fusing inertial measurement unit (IMU) and UWB measurements. The experimental results show the feasibility of the designed controller in practice. The comparative experiments with PD and PD loop demonstrate the robustness of the proposed control method. PMID:28925984

  8. Feedback Robust Cubature Kalman Filter for Target Tracking Using an Angle Sensor.

    Science.gov (United States)

    Wu, Hao; Chen, Shuxin; Yang, Binfeng; Chen, Kun

    2016-05-09

    The direction of arrival (DOA) tracking problem based on an angle sensor is an important topic in many fields. In this paper, a nonlinear filter named the feedback M-estimation based robust cubature Kalman filter (FMR-CKF) is proposed to deal with measurement outliers from the angle sensor. The filter designs a new equivalent weight function with the Mahalanobis distance to combine the cubature Kalman filter (CKF) with the M-estimation method. Moreover, by embedding a feedback strategy which consists of a splitting and merging procedure, the proper sub-filter (the standard CKF or the robust CKF) can be chosen in each time index. Hence, the probability of the outliers' misjudgment can be reduced. Numerical experiments show that the FMR-CKF performs better than the CKF and conventional robust filters in terms of accuracy and robustness with good computational efficiency. Additionally, the filter can be extended to the nonlinear applications using other types of sensors.

  9. Track-to-track association for object matching in an inter-vehicle communication system

    Science.gov (United States)

    Yuan, Ting; Roth, Tobias; Chen, Qi; Breu, Jakob; Bogdanovic, Miro; Weiss, Christian A.

    2015-09-01

    Autonomous driving poses unique challenges for vehicle environment perception due to the complex driving environment the autonomous vehicle finds itself in and differentiates from remote vehicles. Due to inherent uncertainty of the traffic environments and incomplete knowledge due to sensor limitation, an autonomous driving system using only local onboard sensor information is generally not sufficiently enough for conducting a reliable intelligent driving with guaranteed safety. In order to overcome limitations of the local (host) vehicle sensing system and to increase the likelihood of correct detections and classifications, collaborative information from cooperative remote vehicles could substantially facilitate effectiveness of vehicle decision making process. Dedicated Short Range Communication (DSRC) system provides a powerful inter-vehicle wireless communication channel to enhance host vehicle environment perceiving capability with the aid of transmitted information from remote vehicles. However, there is a major challenge before one can fuse the DSRC-transmitted remote information and host vehicle Radar-observed information (in the present case): the remote DRSC data must be correctly associated with the corresponding onboard Radar data; namely, an object matching problem. Direct raw data association (i.e., measurement-to-measurement association - M2MA) is straightforward but error-prone, due to inherent uncertain nature of the observation data. The uncertainties could lead to serious difficulty in matching decision, especially, using non-stationary data. In this study, we present an object matching algorithm based on track-to-track association (T2TA) and evaluate the proposed approach with prototype vehicles in real traffic scenarios. To fully exploit potential of the DSRC system, only GPS position data from remote vehicle are used in fusion center (at host vehicle), i.e., we try to get what we need from the least amount of information; additional feature

  10. Robust three-dimensional object definition in CT and MRI.

    Science.gov (United States)

    Bland, P H; Meyer, C R

    1996-01-01

    This work describes the application of an object definition algorithm to the medical imaging environment for the task of automated detection of anatomical boundaries in three dimensions in the presence of low spatial frequency nonstationarities. We have chosen the Liou-Jain algorithm and have modified it for use with 3D medical image datasets and extended it by including a recruitment operator that corrects for the algorithm's inherent volume underestimation. The algorithm avoids problems in both traditional statistical segmentation and 2D techniques and elegantly bridges the gap between traditional gradient-based edge finding and regression-based segmentation techniques. Results are shown for MRI datasets from the human abdomen and brain and for a CT dataset of a liver tumor, as well as an MRI scan of a glioma in a rat brain. For comparison, the human abdomen dataset was processed by a multivariate, statistical classifier. The results demonstrate the statistical technique's susceptibility to low spatial frequency nonstationarities due to rf field inhomogeneity; the Liou-Jain algorithm is shown to be immune to this effect. Further, the results show spatial consistency as a result of inherent characteristics of the algorithm. Volumes identified by the algorithm are visualized and assessed qualitatively in three dimensions. Quantitative accuracy of the algorithm's volume estimates is assessed by the use of a phantom. This work demonstrates that this technique is effective in automatically detecting anatomical organ and lesion surfaces in 3D medical datasets that are corrupted by low spatial frequency nonstationarity and in obtaining volume estimates.

  11. Distributed and Robust Tracking by Exploiting Set-Membership and Sparsity

    Science.gov (United States)

    Farahmand, Shahrokh

    2011-12-01

    Target tracking research and development are of major importance and continuously expanding interest to a gamut of traditional and emerging applications, which include radar- and sonar-based systems, surveillance and habitat monitoring using distributed wireless sensors, collision avoidance modules envisioned for modern transportation systems, and mobile robot localization and navigation in static and dynamically changing environments, to name a few. This thesis contributes in several issues pertaining to robustness and distributed operation of modern tracking systems. The first issue addressed relates to measurement model nonlinearity. It turns out that by adopting a grid to describe the surveillance region, the nonlinear measurement model can be cast as a linear one at the cost of increasing state dimensionality. However, by exploiting sparsity of the state in this higher dimension, novel approaches are developed for tracking target signal strengths on a grid (TSSG). In multi-target settings, the proposed sparsity-aware TSSG trackers can bypass the challenge of data association and do not require knowing the number of targets present. To obtain individual target tracks when needed, simple data association techniques are also introduced. Due to the independence of TSSG trackers from the data association stage, association errors do not influence TSSG tracking performance. Mitigating the effect of outliers appearing in the state and measurements is the second topic addressed in this thesis. The proposed robust algorithm referred to as doubly robust smoother (DRS) jointly estimates the outliers alongside with the state. To enable such joint estimation, sparsity in the outlier domain is exploited by regularizing the adopted criterion with the ℓ 1-norm of the outlier vector. Through novel methods for parameter tuning, DRS is capable of coping with even high levels of outlier contamination. To ensure low-complexity implementation, iterative coordinate descent and

  12. Robust cell tracking in epithelial tissues through identification of maximum common subgraphs.

    Science.gov (United States)

    Kursawe, Jochen; Bardenet, Rémi; Zartman, Jeremiah J; Baker, Ruth E; Fletcher, Alexander G

    2016-11-01

    Tracking of cells in live-imaging microscopy videos of epithelial sheets is a powerful tool for investigating fundamental processes in embryonic development. Characterizing cell growth, proliferation, intercalation and apoptosis in epithelia helps us to understand how morphogenetic processes such as tissue invagination and extension are locally regulated and controlled. Accurate cell tracking requires correctly resolving cells entering or leaving the field of view between frames, cell neighbour exchanges, cell removals and cell divisions. However, current tracking methods for epithelial sheets are not robust to large morphogenetic deformations and require significant manual interventions. Here, we present a novel algorithm for epithelial cell tracking, exploiting the graph-theoretic concept of a 'maximum common subgraph' to track cells between frames of a video. Our algorithm does not require the adjustment of tissue-specific parameters, and scales in sub-quadratic time with tissue size. It does not rely on precise positional information, permitting large cell movements between frames and enabling tracking in datasets acquired at low temporal resolution due to experimental constraints such as phototoxicity. To demonstrate the method, we perform tracking on the Drosophila embryonic epidermis and compare cell-cell rearrangements to previous studies in other tissues. Our implementation is open source and generally applicable to epithelial tissues. © 2016 The Authors.

  13. An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks.

    Science.gov (United States)

    Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

    2017-03-20

    In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.

  14. An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks

    Science.gov (United States)

    Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

    2017-01-01

    In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods. PMID:28335537

  15. A New Robust Tracking Control Design for Turbofan Engines: H∞/Leitmann Approach

    Directory of Open Access Journals (Sweden)

    Muxuan Pan

    2017-04-01

    Full Text Available In this paper, a H ∞ /Leitmann approach to the robust tracking control design is presented for an uncertain dynamic system. This new method is developed in the following two steps. Firstly, a tracking dynamic system with simultaneous consideration of parameter uncertainty and noise is modeled based on a linear system and a reference model. Accordingly, a “nominal system” from the tracking system is defined and controlled by a H ∞ control to obtain the asymptotical stability and noise resistance. Secondly, by making use of a Lyapunov function and the norm boundedness, a new robust control with the “Leitmann approach” is designed to cope with the uncertainty. The two controls collaborate with each other to achieve “uniform tracking boundedness” and “uniform ultimate tracking boundedness”. The new approach is then applied to an aircraft turbofan control design, and the numerical simulation results show the prescribed performances of the closed-loop system and the advantage of the developed approach.

  16. Robust tracking of dexterous continuum robots: Fusing FBG shape sensing and stereo vision.

    Science.gov (United States)

    Rumei Zhang; Hao Liu; Jianda Han

    2017-07-01

    Robust and efficient tracking of continuum robots is important for improving patient safety during space-confined minimally invasive surgery, however, it has been a particularly challenging task for researchers. In this paper, we present a novel tracking scheme by fusing fiber Bragg grating (FBG) shape sensing and stereo vision to estimate the position of continuum robots. Previous visual tracking easily suffers from the lack of robustness and leads to failure, while the FBG shape sensor can only reconstruct the local shape with integral cumulative error. The proposed fusion is anticipated to compensate for their shortcomings and improve the tracking accuracy. To verify its effectiveness, the robots' centerline is recognized by morphology operation and reconstructed by stereo matching algorithm. The shape obtained by FBG sensor is transformed into distal tip position with respect to the camera coordinate system through previously calibrated registration matrices. An experimental platform was set up and repeated tracking experiments were carried out. The accuracy estimated by averaging the absolute positioning errors between shape sensing and stereo vision is 0.67±0.65 mm, 0.41±0.25 mm, 0.72±0.43 mm for x, y and z, respectively. Results indicate that the proposed fusion is feasible and can be used for closed-loop control of continuum robots.

  17. Robust Regulation and Tracking Control of a Class of Uncertain 2DOF Underactuated Mechanical Systems

    Directory of Open Access Journals (Sweden)

    David I. Rosas Almeida

    2015-01-01

    Full Text Available A strategy to design and implement a robust controller for a class of underactuated mechanical systems, with two degrees of freedom, which solves the problems of regulation and trajectory tracking, is proposed. This control strategy considers the partial measurement of the state vector and the presence of parametric uncertainties in the plant; these conditions are common in the implementation of a control system. The strategy is based on the use of robust finite time convergence observers to estimate the unmeasured state variables, unknown disturbances, and other signals needed for the control system implementation. The performance of the control strategy is illustrated numerically and experimentally.

  18. Hough forests for object detection, tracking, and action recognition.

    Science.gov (United States)

    Gall, Juergen; Yao, Angela; Razavi, Nima; Van Gool, Luc; Lempitsky, Victor

    2011-11-01

    Abstract—The paper introduces Hough forests, which are random forests adapted to perform a generalized Hough transform in an efficient way. Compared to previous Hough-based systems such as implicit shape models, Hough forests improve the performance of the generalized Hough transform for object detection on a categorical level. At the same time, their flexibility permits extensions of the Hough transform to new domains such as object tracking and action recognition. Hough forests can be regarded as task-adapted codebooks of local appearance that allow fast supervised training and fast matching at test time. They achieve high detection accuracy since the entries of such codebooks are optimized to cast Hough votes with small variance and since their efficiency permits dense sampling of local image patches or video cuboids during detection. The efficacy of Hough forests for a set of computer vision tasks is validated through experiments on a large set of publicly available benchmark data sets and comparisons with the state-of-the-art.

  19. Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments

    Science.gov (United States)

    Marrón-Romera, Marta; García, Juan C.; Sotelo, Miguel A.; Pizarro, Daniel; Mazo, Manuel; Cañas, José M.; Losada, Cristina; Marcos, Álvaro

    2010-01-01

    This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found. PMID:22163385

  20. Stereo vision tracking of multiple objects in complex indoor environments.

    Science.gov (United States)

    Marrón-Romera, Marta; García, Juan C; Sotelo, Miguel A; Pizarro, Daniel; Mazo, Manuel; Cañas, José M; Losada, Cristina; Marcos, Alvaro

    2010-01-01

    This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

  1. Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments

    Directory of Open Access Journals (Sweden)

    Álvaro Marcos

    2010-09-01

    Full Text Available This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

  2. Object Tracking Using Local Multiple Features and a Posterior Probability Measure

    Directory of Open Access Journals (Sweden)

    Wenhua Guo

    2017-03-01

    Full Text Available Object tracking has remained a challenging problem in recent years. Most of the trackers can not work well, especially when dealing with problems such as similarly colored backgrounds, object occlusions, low illumination, or sudden illumination changes in real scenes. A centroid iteration algorithm using multiple features and a posterior probability criterion is presented to solve these problems. The model representation of the object and the similarity measure are two key factors that greatly influence the performance of the tracker. Firstly, this paper propose using a local texture feature which is a generalization of the local binary pattern (LBP descriptor, which we call the double center-symmetric local binary pattern (DCS-LBP. This feature shows great discrimination between similar regions and high robustness to noise. By analyzing DCS-LBP patterns, a simplified DCS-LBP is used to improve the object texture model called the SDCS-LBP. The SDCS-LBP is able to describe the primitive structural information of the local image such as edges and corners. Then, the SDCS-LBP and the color are combined to generate the multiple features as the target model. Secondly, a posterior probability measure is introduced to reduce the rate of matching mistakes. Three strategies of target model update are employed. Experimental results show that our proposed algorithm is effective in improving tracking performance in complicated real scenarios compared with some state-of-the-art methods.

  3. Extending Track Analysis from Animals in the Lab to Moving Objects Anywhere

    NARCIS (Netherlands)

    Dommelen, W. van; Laar, P.J.L.J. van de; Noldus, L.P.J.J.

    2013-01-01

    In this chapter we compare two application domains in which the tracking of objects and the analysis of their movements are core activities, viz. animal tracking and vessel tracking. More specifically, we investigate whether EthoVision XT, a research tool for video tracking and analysis of the

  4. A Robust Vision-based Runway Detection and Tracking Algorithm for Automatic UAV Landing

    KAUST Repository

    Abu Jbara, Khaled F.

    2015-05-01

    This work presents a novel real-time algorithm for runway detection and tracking applied to the automatic takeoff and landing of Unmanned Aerial Vehicles (UAVs). The algorithm is based on a combination of segmentation based region competition and the minimization of a specific energy function to detect and identify the runway edges from streaming video data. The resulting video-based runway position estimates are updated using a Kalman Filter, which can integrate other sensory information such as position and attitude angle estimates to allow a more robust tracking of the runway under turbulence. We illustrate the performance of the proposed lane detection and tracking scheme on various experimental UAV flights conducted by the Saudi Aerospace Research Center. Results show an accurate tracking of the runway edges during the landing phase under various lighting conditions. Also, it suggests that such positional estimates would greatly improve the positional accuracy of the UAV during takeoff and landing phases. The robustness of the proposed algorithm is further validated using Hardware in the Loop simulations with diverse takeoff and landing videos generated using a commercial flight simulator.

  5. Robust Speed Tracking of Induction Motors: An Arduino-Implemented Intelligent Control Approach

    Directory of Open Access Journals (Sweden)

    Tan-Jan Ho

    2018-01-01

    Full Text Available To feasibly achieve economical and satisfactory robust velocity tracking of an induction machine (IM, we propose an Arduino-implemented intelligent speed controller. Because a voltage/frequency controlled IM framework is simple and well suited for being controlled by the proposed speed controller, it is adopted herein. Taking into account easy implementation and good performance, we design the controller using a modified Ziegler-Nichols PID (modified Z-N PID and a fuzzy logic controller (FLC. The modified Z-N PID and the FLC are connected in tandem. The latter is designed based on the output signal of the former for adaptively yielding adequate torque commands. Experimental results of IM velocity tracking controlled by our PC-based and Arduino-based speed controllers consistently show that the proposed design scheme can yield remarkable tracking performance and robustness. In addition, it is demonstrated that the proposed Arduino-implemented controller is not only viable but also effective in terms of cost, size and tracking performance.

  6. Robustness of serial clustering of extratropical cyclones to the choice of tracking method

    Directory of Open Access Journals (Sweden)

    Joaquim G. Pinto

    2016-07-01

    Full Text Available Cyclone clusters are a frequent synoptic feature in the Euro-Atlantic area. Recent studies have shown that serial clustering of cyclones generally occurs on both flanks and downstream regions of the North Atlantic storm track, while cyclones tend to occur more regulary on the western side of the North Atlantic basin near Newfoundland. This study explores the sensitivity of serial clustering to the choice of cyclone tracking method using cyclone track data from 15 methods derived from ERA-Interim data (1979–2010. Clustering is estimated by the dispersion (ratio of variance to mean of winter [December – February (DJF] cyclone passages near each grid point over the Euro-Atlantic area. The mean number of cyclone counts and their variance are compared between methods, revealing considerable differences, particularly for the latter. Results show that all different tracking methods qualitatively capture similar large-scale spatial patterns of underdispersion and overdispersion over the study region. The quantitative differences can primarily be attributed to the differences in the variance of cyclone counts between the methods. Nevertheless, overdispersion is statistically significant for almost all methods over parts of the eastern North Atlantic and Western Europe, and is therefore considered as a robust feature. The influence of the North Atlantic Oscillation (NAO on cyclone clustering displays a similar pattern for all tracking methods, with one maximum near Iceland and another between the Azores and Iberia. The differences in variance between methods are not related with different sensitivities to the NAO, which can account to over 50% of the clustering in some regions. We conclude that the general features of underdispersion and overdispersion of extratropical cyclones over the North Atlantic and Western Europe are robust to the choice of tracking method. The same is true for the influence of the NAO on cyclone dispersion.

  7. How many objects are you worth? Quantification of the self-motion load on multiple object tracking

    Directory of Open Access Journals (Sweden)

    Laura Elizabeth Thomas

    2011-09-01

    Full Text Available Perhaps walking and chewing gum is effortless, but walking and tracking moving objects is not. Multiple object tracking is impaired by walking from one location to another, suggesting that updating location of the self puts demands on object tracking processes. Here, we quantified the cost of self-motion in terms of the tracking load. Participants in a virtual environment tracked a variable number of targets (1-5 among distractors while either staying in one place or moving along a path that was similar to the objects’ motion. At the end of each trial, participants decided whether a probed dot was a target or distractor. As in our previous work, self-motion significantly impaired performance in tracking multiple targets. Quantifying tracking capacity for each individual under move versus stay conditions further revealed that self-motion during tracking produced a cost to capacity of about 0.8 (±0.2 objects. Tracking your own motion is worth about one object, suggesting that updating the location of the self is similar, but perhaps slightly easier, than updating locations of objects.

  8. Tracking Deforming Objects using Particle Filtering for Geometric Active Contours

    National Research Council Canada - National Science Library

    Rathi, Yogesh; Vaswani, Namrata; Tannenbaum, Allen; Yezzi, Anthony

    2007-01-01

    .... Tracking algorithms using Kalman filters or particle filters have been proposed for finite dimensional representations of shape, but these are dependent on the chosen parametrization and cannot...

  9. Feature Classification for Robust Shape-Based Collaborative Tracking and Model Updating

    Directory of Open Access Journals (Sweden)

    C. S. Regazzoni

    2008-09-01

    Full Text Available A new collaborative tracking approach is introduced which takes advantage of classified features. The core of this tracker is a single tracker that is able to detect occlusions and classify features contributing in localizing the object. Features are classified in four classes: good, suspicious, malicious, and neutral. Good features are estimated to be parts of the object with a high degree of confidence. Suspicious ones have a lower, yet significantly high, degree of confidence to be a part of the object. Malicious features are estimated to be generated by clutter, while neutral features are characterized with not a sufficient level of uncertainty to be assigned to the tracked object. When there is no occlusion, the single tracker acts alone, and the feature classification module helps it to overcome distracters such as still objects or little clutter in the scene. When more than one desired moving objects bounding boxes are close enough, the collaborative tracker is activated and it exploits the advantages of the classified features to localize each object precisely as well as updating the objects shape models more precisely by assigning again the classified features to the objects. The experimental results show successful tracking compared with the collaborative tracker that does not use the classified features. Moreover, more precise updated object shape models will be shown.

  10. A Mobile Service Oriented Multiple Object Tracking Augmented Reality Architecture for Education and Learning Experiences

    Science.gov (United States)

    Rattanarungrot, Sasithorn; White, Martin; Newbury, Paul

    2014-01-01

    This paper describes the design of our service-oriented architecture to support mobile multiple object tracking augmented reality applications applied to education and learning scenarios. The architecture is composed of a mobile multiple object tracking augmented reality client, a web service framework, and dynamic content providers. Tracking of…

  11. Swarming visual sensor network for real-time multiple object tracking

    Science.gov (United States)

    Baranov, Yuri P.; Yarishev, Sergey N.; Medvedev, Roman V.

    2016-04-01

    Position control of multiple objects is one of the most actual problems in various technology areas. For example, in construction area this problem is represented as multi-point deformation control of bearing constructions in order to prevent collapse, in mining - deformation control of lining constructions, in rescue operations - potential victims and sources of ignition location, in transport - traffic control and traffic violations detection, in robotics -traffic control for organized group of robots and many other problems in different areas. Usage of stationary devices for solving these problems is inappropriately due to complex and variable geometry of control areas. In these cases self-organized systems of moving visual sensors is the best solution. This paper presents a concept of scalable visual sensor network with swarm architecture for multiple object pose estimation and real-time tracking. In this article recent developments of distributed measuring systems were reviewed with consequent investigation of advantages and disadvantages of existing systems, whereupon theoretical principles of design of swarming visual sensor network (SVSN) were declared. To measure object coordinates in the world coordinate system using TV-camera intrinsic (focal length, pixel size, principal point position, distortion) and extrinsic (rotation matrix, translation vector) calibration parameters were needed to be determined. Robust camera calibration was a too resource-intensive task for using moving camera. In this situation position of the camera is usually estimated using a visual mark with known parameters. All measurements were performed in markcentered coordinate systems. In this article a general adaptive algorithm of coordinate conversion of devices with various intrinsic parameters was developed. Various network topologies were reviewed. Minimum error in objet tracking was realized by finding the shortest path between object of tracking and bearing sensor, which set

  12. Robust kernel-based tracking with multiple subtemplates in vision guidance system.

    Science.gov (United States)

    Yan, Yuzhuang; Huang, Xinsheng; Xu, Wanying; Shen, Lurong

    2012-01-01

    The mean shift algorithm has achieved considerable success in target tracking due to its simplicity and robustness. However, the lack of spatial information may result in its failure to get high tracking precision. This might be even worse when the target is scale variant and the sequences are gray-levels. This paper presents a novel multiple subtemplates based tracking algorithm for the terminal guidance application. By applying a separate tracker to each subtemplate, it can handle more complicated situations such as rotation, scaling, and partial coverage of the target. The innovations include: (1) an optimal subtemplates selection algorithm is designed, which ensures that the selected subtemplates maximally represent the information of the entire template while having the least mutual redundancy; (2) based on the serial tracking results and the spatial constraint prior to those subtemplates, a Gaussian weighted voting method is proposed to locate the target center; (3) the optimal scale factor is determined by maximizing the voting results among the scale searching layers, which avoids the complicated threshold setting problem. Experiments on some videos with static scenes show that the proposed method greatly improves the tracking accuracy compared to the original mean shift algorithm.

  13. Robust Kernel-Based Tracking with Multiple Subtemplates in Vision Guidance System

    Directory of Open Access Journals (Sweden)

    Lurong Shen

    2012-02-01

    Full Text Available The mean shift algorithm has achieved considerable success in target tracking due to its simplicity and robustness. However, the lack of spatial information may result in its failure to get high tracking precision. This might be even worse when the target is scale variant and the sequences are gray-levels. This paper presents a novel multiple subtemplates based tracking algorithm for the terminal guidance application. By applying a separate tracker to each subtemplate, it can handle more complicated situations such as rotation, scaling, and partial coverage of the target. The innovations include: (1 an optimal subtemplates selection algorithm is designed, which ensures that the selected subtemplates maximally represent the information of the entire template while having the least mutual redundancy; (2 based on the serial tracking results and the spatial constraint prior to those subtemplates, a Gaussian weighted voting method is proposed to locate the target center; (3 the optimal scale factor is determined by maximizing the voting results among the scale searching layers, which avoids the complicated threshold setting problem. Experiments on some videos with static scenes show that the proposed method greatly improves the tracking accuracy compared to the original mean shift algorithm.

  14. A data set for evaluating the performance of multi-class multi-object video tracking

    OpenAIRE

    Chakraborty, Avishek; Stamatescu, Victor; Wong, Sebastien C.; Wigley, Grant; Kearney, David

    2017-01-01

    One of the challenges in evaluating multi-object video detection, tracking and classification systems is having publically available data sets with which to compare different systems. However, the measures of performance for tracking and classification are different. Data sets that are suitable for evaluating tracking systems may not be appropriate for classification. Tracking video data sets typically only have ground truth track IDs, while classification video data sets only have ground tru...

  15. Image Acquisition of Robust Vision Systems to Monitor Blurred Objects in Hazy Smoking Environments

    Energy Technology Data Exchange (ETDEWEB)

    Ahn, Yongjin; Park, Seungkyu; Baik, Sunghoon; Kim, Donglyul; Nam, Sungmo; Jeong, Kyungmin [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2014-05-15

    Image information in disaster area or radiation area of nuclear industry is an important data for safety inspection and preparing appropriate damage control plans. So, robust vision system for structures and facilities in blurred smoking environments, such as the places of a fire and detonation, is essential in remote monitoring. Vision systems can't acquire an image when the illumination light is blocked by disturbance materials, such as smoke, fog, dust. The vision system based on wavefront correction can be applied to blurred imaging environments and the range-gated imaging system can be applied to both of blurred imaging and darken light environments. Wavefront control is a widely used technique to improve the performance of optical systems by actively correcting wavefront distortions, such as atmospheric turbulence, thermally-induced distortions, and laser or laser device aberrations, which can reduce the peak intensity and smear an acquired image. The principal applications of wavefront control are for improving the image quality in optical imaging systems such as infrared astronomical telescopes, in imaging and tracking rapidly moving space objects, and in compensating for laser beam distortion through the atmosphere. A conventional wavefront correction system consists of a wavefront sensor, a deformable mirror and a control computer. The control computer measures the wavefront distortions using a wavefront sensor and corrects it using a deformable mirror in a closed-loop. Range-gated imaging (RGI) is a direct active visualization technique using a highly sensitive image sensor and a high intensity illuminant. Currently, the range-gated imaging technique providing 2D and 3D images is one of emerging active vision technologies. The range-gated imaging system gets vision information by summing time sliced vision images. In the RGI system, a high intensity illuminant illuminates for ultra-short time and a highly sensitive image sensor is gated by ultra

  16. Tracking objects with fixed-wing UAV using model predictive control and machine vision

    OpenAIRE

    Skjong, Espen; Nundal, Stian Aas

    2014-01-01

    This thesis describes the development of an object tracking system for unmanned aerial vehicles (UAVs), intended to be used for search and rescue (SAR) missions. The UAV is equipped with a two-axis gimbal system, which houses an infrared (IR) camera used to detect and track objects of interest, and a lower level autopilot. An external computer vision (CV) module is assumed implemented and connected to the object tracking system, providing object positions and velocities to the control system....

  17. Adaptive low-rank subspace learning with online optimization for robust visual tracking.

    Science.gov (United States)

    Liu, Risheng; Wang, Di; Han, Yuzhuo; Fan, Xin; Luo, Zhongxuan

    2017-04-01

    In recent years, sparse and low-rank models have been widely used to formulate appearance subspace for visual tracking. However, most existing methods only consider the sparsity or low-rankness of the coefficients, which is not sufficient enough for appearance subspace learning on complex video sequences. Moreover, as both the low-rank and the column sparse measures are tightly related to all the samples in the sequences, it is challenging to incrementally solve optimization problems with both nuclear norm and column sparse norm on sequentially obtained video data. To address above limitations, this paper develops a novel low-rank subspace learning with adaptive penalization (LSAP) framework for subspace based robust visual tracking. Different from previous work, which often simply decomposes observations as low-rank features and sparse errors, LSAP simultaneously learns the subspace basis, low-rank coefficients and column sparse errors to formulate appearance subspace. Within LSAP framework, we introduce a Hadamard production based regularization to incorporate rich generative/discriminative structure constraints to adaptively penalize the coefficients for subspace learning. It is shown that such adaptive penalization can significantly improve the robustness of LSAP on severely corrupted dataset. To utilize LSAP for online visual tracking, we also develop an efficient incremental optimization scheme for nuclear norm and column sparse norm minimizations. Experiments on 50 challenging video sequences demonstrate that our tracker outperforms other state-of-the-art methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Tracking error constrained robust adaptive neural prescribed performance control for flexible hypersonic flight vehicle

    Directory of Open Access Journals (Sweden)

    Zhonghua Wu

    2017-02-01

    Full Text Available A robust adaptive neural control scheme based on a back-stepping technique is developed for the longitudinal dynamics of a flexible hypersonic flight vehicle, which is able to ensure the state tracking error being confined in the prescribed bounds, in spite of the existing model uncertainties and actuator constraints. Minimal learning parameter technique–based neural networks are used to estimate the model uncertainties; thus, the amount of online updated parameters is largely lessened, and the prior information of the aerodynamic parameters is dispensable. With the utilization of an assistant compensation system, the problem of actuator constraint is overcome. By combining the prescribed performance function and sliding mode differentiator into the neural back-stepping control design procedure, a composite state tracking error constrained adaptive neural control approach is presented, and a new type of adaptive law is constructed. As compared with other adaptive neural control designs for hypersonic flight vehicle, the proposed composite control scheme exhibits not only low-computation property but also strong robustness. Finally, two comparative simulations are performed to demonstrate the robustness of this neural prescribed performance controller.

  19. A robust multi-objective global supplier selection model under currency fluctuation and price discount

    Science.gov (United States)

    Zarindast, Atousa; Seyed Hosseini, Seyed Mohamad; Pishvaee, Mir Saman

    2017-11-01

    Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss decision variables, respectively, by a two-stage stochastic planning model, a robust stochastic optimization planning model which integrates worst case scenario in modeling approach and finally by equivalent deterministic planning model. The experimental study is carried out to compare the performances of the three models. Robust model resulted in remarkable cost saving and it illustrated that to cope with such uncertainties, we should consider them in advance in our planning. In our case study different supplier were selected due to this uncertainties and since supplier selection is a strategic decision, it is crucial to consider these uncertainties in planning approach.

  20. Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor

    Directory of Open Access Journals (Sweden)

    Lvwen Huang

    2017-08-01

    Full Text Available Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields.

  1. Hyperspectral Foveated Imaging Sensor for Objects Identification and Tracking Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Optical tracking and identification sensors have numerous NASA and non-NASA applications. For example, airborne or spaceborne imaging sensors are used to visualize...

  2. Robust and Rapid Air-Borne Odor Tracking without Casting1,2,3

    Science.gov (United States)

    Bhattacharyya, Urvashi

    2015-01-01

    Abstract Casting behavior (zigzagging across an odor stream) is common in air/liquid-borne odor tracking in open fields; however, terrestrial odor localization often involves path selection in a familiar environment. To study this, we trained rats to run toward an odor source in a multi-choice olfactory arena with near-laminar airflow. We find that rather than casting, rats run directly toward an odor port, and if this is incorrect, they serially sample other sources. This behavior is consistent and accurate in the presence of perturbations, such as novel odors, background odor, unilateral nostril stitching, and turbulence. We developed a model that predicts that this run-and-scan tracking of air-borne odors is faster than casting, provided there are a small number of targets at known locations. Thus, the combination of best-guess target selection with fallback serial sampling provides a rapid and robust strategy for finding odor sources in familiar surroundings. PMID:26665165

  3. Internal Model-Based Robust Tracking Control Design for the MEMS Electromagnetic Micromirror.

    Science.gov (United States)

    Tan, Jiazheng; Sun, Weijie; Yeow, John T W

    2017-05-26

    The micromirror based on micro-electro-mechanical systems (MEMS) technology is widely employed in different areas, such as scanning, imaging and optical switching. This paper studies the MEMS electromagnetic micromirror for scanning or imaging application. In these application scenarios, the micromirror is required to track the command sinusoidal signal, which can be converted to an output regulation problem theoretically. In this paper, based on the internal model principle, the output regulation problem is solved by designing a robust controller that is able to force the micromirror to track the command signal accurately. The proposed controller relies little on the accuracy of the model. Further, the proposed controller is implemented, and its effectiveness is examined by experiments. The experimental results demonstrate that the performance of the proposed controller is satisfying.

  4. Robust Redundant Input Reliable Tracking Control for Omnidirectional Rehabilitative Training Walker

    Directory of Open Access Journals (Sweden)

    Ping Sun

    2014-01-01

    Full Text Available The problem of robust reliable tracking control on the omnidirectional rehabilitative training walker is examined. The new nonlinear redundant input method is proposed when one wheel actuator fault occurs. The aim of the study is to design an asymptotically stable controller that can guarantee the safety of the user and ensure tracking on a training path planned by a physical therapist. The redundant degrees of freedom safety control and the asymptotically zero state detectable concept of the walker are presented, the model of redundant degree is constructed, and the property of center of gravity constant shift is obtained. A controller that can satisfy asymptotic stability is obtained using a common Lyapunov function for admissible uncertainties resulting from an actuator fault. Simulation results confirm the effectiveness of the proposed method and verify that the walker can provide safe sequential motion when one wheel actuator is at fault.

  5. A Frequency-Tracking and Impedance-Matching Combined System for Robust Wireless Power Transfer

    Directory of Open Access Journals (Sweden)

    Yanting Luo

    2017-01-01

    Full Text Available One of the greatest challenges to power embedded devices using magnetically coupled resonant wireless power transfer (WPT system is that the amount of power delivered to the load is very sensitive to load impedance variations. Previous adaptive impedance-matching (IM technologies have drawbacks because adding IM networks, relay coils, or other compensating components in the receiver-side will significantly increase the receiver size. In this paper, a novel frequency-tracking and impedance-matching combined system is proposed to improve the robustness of wireless power transfer for embedded devices. The characteristics of the improved WPT system are investigated theoretically based on the two-port network model. Simulation and experimental studies are carried out to validate the proposed system. The results suggest that the frequency-tracking and impedance-matching combined WPT system can quickly find the best matching points and maintain high power transmission efficiency and output power when the load impedance changes.

  6. Human-like object tracking and gaze estimation with PKD android

    Science.gov (United States)

    Wijayasinghe, Indika B.; Miller, Haylie L.; Das, Sumit K.; Bugnariu, Nicoleta L.; Popa, Dan O.

    2016-05-01

    As the use of robots increases for tasks that require human-robot interactions, it is vital that robots exhibit and understand human-like cues for effective communication. In this paper, we describe the implementation of object tracking capability on Philip K. Dick (PKD) android and a gaze tracking algorithm, both of which further robot capabilities with regard to human communication. PKD's ability to track objects with human-like head postures is achieved with visual feedback from a Kinect system and an eye camera. The goal of object tracking with human-like gestures is twofold: to facilitate better human-robot interactions and to enable PKD as a human gaze emulator for future studies. The gaze tracking system employs a mobile eye tracking system (ETG; SensoMotoric Instruments) and a motion capture system (Cortex; Motion Analysis Corp.) for tracking the head orientations. Objects to be tracked are displayed by a virtual reality system, the Computer Assisted Rehabilitation Environment (CAREN; MotekForce Link). The gaze tracking algorithm converts eye tracking data and head orientations to gaze information facilitating two objectives: to evaluate the performance of the object tracking system for PKD and to use the gaze information to predict the intentions of the user, enabling the robot to understand physical cues by humans.

  7. Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND

    Directory of Open Access Journals (Sweden)

    COJBASIC, Z.

    2011-11-01

    Full Text Available A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction is driven to a desired result. Reliable feature extraction is necessary to fully exploit a neuro-fuzzy classifier which is the core of the proposed 2D object recognition method, predecessor of 3D object reconstruction. Experimental results on the rehabilitation assistive robotic system FRIEND demonstrate the effectiveness of the proposed method.

  8. Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

    Science.gov (United States)

    Cho, Youngjun; Julier, Simon J.; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

    2017-01-01

    The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the

  9. Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging.

    Science.gov (United States)

    Cho, Youngjun; Julier, Simon J; Marquardt, Nicolai; Bianchi-Berthouze, Nadia

    2017-10-01

    The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the

  10. Tracking of objectively measured physical activity from childhood to adolescence

    DEFF Research Database (Denmark)

    Kristensen, Peter Lund; Møller, N C; Korsholm, L

    2007-01-01

    A number of studies have investigated tracking of physical activity from childhood to adolescence and, in general, these studies have been based on methods with some degree of subjectivity (e.g., questionnaires). The aim of the present study was to evaluate tracking of physical activity from...... childhood to adolescence using accelerometry, taking into account major sources of variation in physical activity. Both a crude and an adjusted model was fitted, and, in the adjusted model, analyses were corrected for seasonal variation, within-week variation, activity registration during night time sleep......, in the adjusted model highly significant stability coefficients of 0.53 and 0.48 for boys and girls, respectively, were observed. It was concluded that physical activity behavior tends to track moderately from childhood to adolescence....

  11. Robust optimization of robotic pick and place operations for deformable objects through simulation

    DEFF Research Database (Denmark)

    Bo Jorgensen, Troels; Debrabant, Kristian; Kruger, Norbert

    2016-01-01

    This paper discusses various optimization schemes for partly stochastic and bound optimization, particular with application to solve robotic optimization problems, where robustness of the solutions is crucial. The use case revolves around grasping and manipulation of deformable objects. These kinds...... for the task. The solutions are parameterized in terms of the robot motion and the gripper configuration, and after each simulation various objective scores are determined and combined. This enables the use of various optimization strategies. Based on visual inspection of the most robust solution found......, it is determined that 50 out of 50 simulations, with different meat properties, produce satisfactory manipulations....

  12. Development of multi-objective genetic algorithm concurrent subspace optimization (MOGACSSO) method with robustness

    Science.gov (United States)

    Parashar, Sumeet

    Most engineering design problems are complex and multidisciplinary in nature, and quite often require more than one objective (cost) function to be extremized simultaneously. For multi-objective optimization problems, there is not a single optimum solution, but a set of optimum solutions called the Pareto set. The primary goal of this research is to develop a heuristic solution strategy to enable multi-objective optimization of highly coupled multidisciplinary design applications, wherein each discipline is able to retain some degree of autonomous control during the process. To achieve this goal, this research extends the capability of the Multi-Objective Pareto Concurrent Subspace Optimization (MOPCSSO) method to generate large numbers of non-dominated solutions in each cycle, with subsequent update and refinement, thereby greatly increasing efficiency. While the conventional MOPCSSO approach is easily able to generate Pareto solutions, it will only generate one Pareto solution at a time. In order to generate the complete Pareto front, MOPCSSO requires multiple runs (translating into many system convergence cycles) using different initial staring points. In this research, a Genetic Algorithm-based heuristic solution strategy is developed for multi-objective problems in coupled multidisciplinary design. The Multi-Objective Genetic Algorithm Concurrent Subspace Optimization (MOGACSSO) method allows for the generation of relatively evenly distributed Pareto solutions in a faster and more efficient manner than repeated implementation of MOPCSSO. While achieving an optimum design, it is often also desirable that the optimum design be robust to uncontrolled parameter variations. In this research, the capability of the MOGACSSO method is also extended to generate Pareto points that are robust in terms of performance and feasibility, for given uncontrolled parameter variations. The Roust-MOGACSSO method developed in this research can generate a large number of designs

  13. Robust tracking control of an IPMC actuator using nonsingular terminal sliding mode

    Science.gov (United States)

    Khawwaf, Jasim; Zheng, Jinchuan; Lu, Renquan; Al-Ghanimi, Ali; Kazem, Bahaa I.; Man, Zhihong

    2017-09-01

    Ionic polymer metal composite (IPMC) is a highly innovative material that has recently gained attention in many fields such as medical, biomimetic, and micro/nano underwater applications. The main characteristic of IPMC lies in its ability to achieve a large deflection under a fairly low driving voltage. Moreover, its agile, light weight, noiseless and flexible features render it well suited for certain specific applications. Like other smart materials, such as piezoelectric ceramics, IPMC could be used in actuators or sensors. In this paper, we study the application of IPMC as an actuator for underwater use. The goal is to develop a robust feedback controller for the IPMC actuator to track a desired reference whilst dealing with the uncertainties due to the inherent actuator nonlinearity, external disturbance or the variations of working environment. To this end, we first present a nominal model of the IPMC actuator through experimental identification. Next, a nonsingular terminal sliding mode controller is proposed. Lastly, experimental studies are conducted to verify the tracking accuracy and robustness of the designed controller.

  14. Efficient Tracking of Moving Objects with Precision Guarantees

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian Søndergaard; Nenortaite, Jovita

    2004-01-01

    Sustained advances in wireless communications, geo-positioning, and consumer electronics pave the way to a kind of location-based service that relies on the tracking of the continuously changing positions of an entire population of service users. This type of service is characterized by large...

  15. Efficient Tracking of Moving Objects with Precision Guarantees

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian Søndergaard; Nenortaite, Jovita

    2004-01-01

    We are witnessing continued improvements in wireless communications and geo-positioning. In addition, the performance/price ratio for consumer electronics continues to improve. These developments pave the way to a kind of location-based service that relies on the tracking of the continuously...

  16. Multiscale Architectures and Parallel Algorithms for Video Object Tracking

    Science.gov (United States)

    2011-10-01

    Black River Systems. This may have inadvertently introduced bugs that were later discovered by AFRL during testing (of the June 22, 2011 version of...Parallelism in Algorithms and Architectures, pages 289–298, 2007. [3] S. Ali and M. Shah. COCOA - Tracking in aerial imagery. In Daniel J. Henry

  17. Many Objective Robust Decision Making for Complex Environmental Systems Undergoing Change

    Science.gov (United States)

    Kasprzyk, J. R.; Nataraj, S.; Reed, P. M.; Lempert, R. J.

    2012-12-01

    Water resources planning has traditionally used historical data within benefit-maximizing frameworks for system design. The validity of this approach is threatened by environmental change and population growth, which create deep uncertainties that modify the distributions of data that characterize the system. Furthermore, solutions from the traditional benefit-maximizing approaches may prove inferior when multiple, complex objectives are introduced (e.g., maximizing reliable performance or environmental quality). To address these issues, this presentation introduces a framework termed many objective robust decision making (MORDM), which combines many objective evolutionary optimization, robust decision making (RDM), and interactive visual analytics to facilitate the management of complex environmental systems. Many objective evolutionary search enables the discovery of the key tradeoffs in complex planning problems. Subsequently RDM is used to determine the robustness of the component solutions within the many objective tradeoffs to deeply uncertain future conditions. Each solution is tested under the ensemble of future extreme states of the world (SOW). Interactive visual analytics are used to explore whether solutions of interest are robust to a wide range of plausible future conditions (i.e., assessment of their Pareto satisficing behavior in alternative SOW). Scenario discovery methods that use statistical data mining algorithms are then used to identify what assumptions and system conditions strongly control the cost-effectiveness, efficiency, and reliability of the robust alternatives. The framework is demonstrated using a case study that examines a single city's water supply in the Lower Rio Grande Valley (LRGV) in Texas, USA. Results suggest that including robustness as a decision criterion can dramatically change the formulation of complex environmental management problems as well as the negotiated selection of candidate alternatives to implement. MORDM

  18. Control design for robust tracking and smooth transition in power systems with battery/supercapacitor hybrid energy storage devices

    Science.gov (United States)

    Jung, Hoeguk; Wang, Haifeng; Hu, Tingshu

    2014-12-01

    This paper considers some control design problems in a power system driven by battery/supercapacitor hybrid energy storage devices. The currents in the battery and the supercapacitor are actively controlled by two bidirectional buck-boost converters. Two control objectives are addressed in this paper: one is to achieve robust tracking of two reference variables, the battery current and the load voltage, the other is to achieve smooth transition of these variables during load switch. Based on the state-space averaged model we newly developed, the control design problems are converted into numerically efficient optimization problems with linear matrix inequality (LMI) constraints. An experimental system is constructed to validate the control design methods.

  19. Robust tracking and distributed synchronization control of a multi-motor servomechanism with H-infinity performance.

    Science.gov (United States)

    Wang, Minlin; Ren, Xuemei; Chen, Qiang

    2017-10-21

    The multi-motor servomechanism (MMS) is a multi-variable, high coupling and nonlinear system, which makes the controller design challenging. In this paper, an adaptive robust H-infinity control scheme is proposed to achieve both the load tracking and multi-motor synchronization of MMS. This control scheme consists of two parts: a robust tracking controller and a distributed synchronization controller. The robust tracking controller is constructed by incorporating a neural network (NN) K-filter observer into the dynamic surface control, while the distributed synchronization controller is designed by combining the mean deviation coupling control strategy with the distributed technique. The proposed control scheme has several merits: 1) by using the mean deviation coupling synchronization control strategy, the tracking controller and the synchronization controller can be designed individually without any coupling problem; 2) the immeasurable states and unknown nonlinearities are handled by a NN K-filter observer, where the number of NN weights is largely reduced by using the minimal learning parameter technique; 3) the H-infinity performances of tracking error and synchronization error are guaranteed by introducing a robust term into the tracking controller and the synchronization controller, respectively. The stabilities of the tracking and synchronization control systems are analyzed by the Lyapunov theory. Simulation and experimental results based on a four-motor servomechanism are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Robust Control of Welding Robot for Tracking a Rectangular Welding Line

    Directory of Open Access Journals (Sweden)

    Manh Dung Ngo

    2008-11-01

    Full Text Available This paper highlights a welding robot (WR for its end effector to track a rectangular welding line (RWL. The WR includes five actuators which use a DC motor as a power source. Two controllers are proposed to control the WR's end effector: a main controller and a servo controller. Firstly, based on WR's kinematic equations and its feedback errors using backstepping method the main controller is proposed to design the reference-inputs for the WR's actuators in order that the WR's end effector tracks the RWL. Secondly, based on the dynamic equation of WR's actuator, the servo controller is designed using an active disturbance rejection control method. Finally, a control system incorporated with the main controller and the servo controllers make the WR's end effector robustly track a RWL in the presence of the modeling uncertainty and disturbances during the welding process. In experiment, the main controller which has a function as a master of the control system links to the five servo controllers which have a function as a slave via I2C communication. The effectiveness of the proposed control system is proven through the simulation and experimental results.

  1. Robust Control of Welding Robot for Tracking a Rectangular Welding Line

    Directory of Open Access Journals (Sweden)

    Manh Dung Ngo

    2006-09-01

    Full Text Available This paper highlights a welding robot (WR for its end effector to track a rectangular welding line (RWL. The WR includes five actuators which use a DC motor as a power source. Two controllers are proposed to control the WR's end effector: a main controller and a servo controller. Firstly, based on WR's kinematic equations and its feedback errors using backstepping method the main controller is proposed to design the reference-inputs for the WR's actuators in order that the WR's end effector tracks the RWL. Secondly, based on the dynamic equation of WR's actuator, the servo controller is designed using an active disturbance rejection control method. Finally, a control system incorporated with the main controller and the servo controllers make the WR's end effector robustly track a RWL in the presence of the modeling uncertainty and disturbances during the welding process. In experiment, the main controller which has a function as a master of the control system links to the five servo controllers which have a function as a slave via I2C communication. The effectiveness of the proposed control system is proven through the simulation and experimental results.

  2. Online multi-modal robust non-negative dictionary learning for visual tracking.

    Science.gov (United States)

    Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

    2015-01-01

    Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

  3. Online multi-modal robust non-negative dictionary learning for visual tracking.

    Directory of Open Access Journals (Sweden)

    Xiang Zhang

    Full Text Available Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

  4. Tracking of Moving Objects in Video Through Invariant Features in Their Graph Representation

    Directory of Open Access Journals (Sweden)

    Averbuch A

    2008-01-01

    Full Text Available Abstract The paper suggests a contour-based algorithm for tracking moving objects in video. The inputs are segmented moving objects. Each segmented frame is transformed into region adjacency graphs (RAGs. The object's contour is divided into subcurves. Contour's junctions are derived. These junctions are the unique “signature� of the tracked object. Junctions from two consecutive frames are matched. The junctions' motion is estimated using RAG edges in consecutive frames. Each pair of matched junctions may be connected by several paths (edges that become candidates that represent a tracked contour. These paths are obtained by the -shortest paths algorithm between two nodes. The RAG is transformed into a weighted directed graph. The final tracked contour construction is derived by a match between edges (subcurves and candidate paths sets. The RAG constructs the tracked contour that enables an accurate and unique moving object representation. The algorithm tracks multiple objects, partially covered (occluded objects, compounded object of merge/split such as players in a soccer game and tracking in a crowded area for surveillance applications. We assume that features of topologic signature of the tracked object stay invariant in two consecutive frames. The algorithm's complexity depends on RAG's edges and not on the image's size.

  5. The research of moving objects behavior detection and tracking algorithm in aerial video

    Science.gov (United States)

    Yang, Le-le; Li, Xin; Yang, Xiao-ping; Li, Dong-hui

    2015-12-01

    The article focuses on the research of moving target detection and tracking algorithm in Aerial monitoring. Study includes moving target detection, moving target behavioral analysis and Target Auto tracking. In moving target detection, the paper considering the characteristics of background subtraction and frame difference method, using background reconstruction method to accurately locate moving targets; in the analysis of the behavior of the moving object, using matlab technique shown in the binary image detection area, analyzing whether the moving objects invasion and invasion direction; In Auto Tracking moving target, A video tracking algorithm that used the prediction of object centroids based on Kalman filtering was proposed.

  6. Steady-state particle tracking in the object-oriented regional groundwater model ZOOMQ3D

    OpenAIRE

    Jackson, C.R.

    2002-01-01

    This report describes the development of a steady-state particle tracking code for use in conjunction with the object-oriented regional groundwater flow model, ZOOMQ3D (Jackson, 2001). Like the flow model, the particle tracking software, ZOOPT, is written using an object-oriented approach to promote its extensibility and flexibility. ZOOPT enables the definition of steady-state pathlines in three dimensions. Particles can be tracked in both the forward and reverse directions en...

  7. Statistical Track-Before-Detect Methods Applied to Faint Optical Observations of Resident Space Objects

    Science.gov (United States)

    Fujimoto, K.; Yanagisawa, T.; Uetsuhara, M.

    Automated detection and tracking of faint objects in optical, or bearing-only, sensor imagery is a topic of immense interest in space surveillance. Robust methods in this realm will lead to better space situational awareness (SSA) while reducing the cost of sensors and optics. They are especially relevant in the search for high area-to-mass ratio (HAMR) objects, as their apparent brightness can change significantly over time. A track-before-detect (TBD) approach has been shown to be suitable for faint, low signal-to-noise ratio (SNR) images of resident space objects (RSOs). TBD does not rely upon the extraction of feature points within the image based on some thresholding criteria, but rather directly takes as input the intensity information from the image file. Not only is all of the available information from the image used, TBD avoids the computational intractability of the conventional feature-based line detection (i.e., "string of pearls") approach to track detection for low SNR data. Implementation of TBD rooted in finite set statistics (FISST) theory has been proposed recently by Vo, et al. Compared to other TBD methods applied so far to SSA, such as the stacking method or multi-pass multi-period denoising, the FISST approach is statistically rigorous and has been shown to be more computationally efficient, thus paving the path toward on-line processing. In this paper, we intend to apply a multi-Bernoulli filter to actual CCD imagery of RSOs. The multi-Bernoulli filter can explicitly account for the birth and death of multiple targets in a measurement arc. TBD is achieved via a sequential Monte Carlo implementation. Preliminary results with simulated single-target data indicate that a Bernoulli filter can successfully track and detect objects with measurement SNR as low as 2.4. Although the advent of fast-cadence scientific CMOS sensors have made the automation of faint object detection a realistic goal, it is nonetheless a difficult goal, as measurements

  8. Robust 3-Dimensional Object Recognition using Stereo Vision and Geometric Hashing

    NARCIS (Netherlands)

    van Dijck, H.A.L.; Korsten, Maarten J.; van der Heijden, Ferdinand

    1996-01-01

    We propose a technique that combines geometric hashing with stereo vision. The idea is to use the robustness of geometric hashing to spurious data to overcome the correspondence problem, while the stereo vision setup enables direct model matching using the 3-D object models. Furthermore, because the

  9. Weighing Efficiency-Robustness in Supply Chain Disruption by Multi-Objective Firefly Algorithm

    Directory of Open Access Journals (Sweden)

    Tong Shu

    2016-03-01

    Full Text Available This paper investigates various supply chain disruptions in terms of scenario planning, including node disruption and chain disruption; namely, disruptions in distribution centers and disruptions between manufacturing centers and distribution centers. Meanwhile, it also focuses on the simultaneous disruption on one node or a number of nodes, simultaneous disruption in one chain or a number of chains and the corresponding mathematical models and exemplification in relation to numerous manufacturing centers and diverse products. Robustness of the design of the supply chain network is examined by weighing efficiency against robustness during supply chain disruptions. Efficiency is represented by operating cost; robustness is indicated by the expected disruption cost and the weighing issue is calculated by the multi-objective firefly algorithm for consistency in the results. It has been shown that the total cost achieved by the optimal target function is lower than that at the most effective time of supply chains. In other words, the decrease of expected disruption cost by improving robustness in supply chains is greater than the increase of operating cost by reducing efficiency, thus leading to cost advantage. Consequently, by approximating the Pareto Front Chart of weighing between efficiency and robustness, enterprises can choose appropriate efficiency and robustness for their longer-term development.

  10. Object Tracking in Frame-Skipping Video Acquired Using Wireless Consumer Cameras

    Directory of Open Access Journals (Sweden)

    Anlong Ming

    2012-10-01

    Full Text Available Object tracking is an important and fundamental task in computer vision and its high-level applications, e.g., intelligent surveillance, motion-based recognition, video indexing, traffic monitoring and vehicle navigation. However, the recent widespread use of wireless consumer cameras often produces low quality videos with frame-skipping and this makes object tracking difficult. Previous tracking methods, for example, generally depend heavily on object appearance or motion continuity and cannot be directly applied to frame-skipping videos. In this paper, we propose an improved particle filter for object tracking to overcome the frame-skipping difficulties. The novelty of our particle filter lies in using the detection result of erratic motion to ameliorate the transition model for a better trial distribution. Experimental results show that the proposed approach improves the tracking accuracy in comparison with the state-of-the-art methods, even when both the object and the consumer are in motion.

  11. Robust multi-objective calibration strategies - possibilities for improving flood forecasting

    Science.gov (United States)

    Krauße, T.; Cullmann, J.; Saile, P.; Schmitz, G. H.

    2012-10-01

    Process-oriented rainfall-runoff models are designed to approximate the complex hydrologic processes within a specific catchment and in particular to simulate the discharge at the catchment outlet. Most of these models exhibit a high degree of complexity and require the determination of various parameters by calibration. Recently, automatic calibration methods became popular in order to identify parameter vectors with high corresponding model performance. The model performance is often assessed by a purpose-oriented objective function. Practical experience suggests that in many situations one single objective function cannot adequately describe the model's ability to represent any aspect of the catchment's behaviour. This is regardless of whether the objective is aggregated of several criteria that measure different (possibly opposite) aspects of the system behaviour. One strategy to circumvent this problem is to define multiple objective functions and to apply a multi-objective optimisation algorithm to identify the set of Pareto optimal or non-dominated solutions. Nonetheless, there is a major disadvantage of automatic calibration procedures that understand the problem of model calibration just as the solution of an optimisation problem: due to the complex-shaped response surface, the estimated solution of the optimisation problem can result in different near-optimum parameter vectors that can lead to a very different performance on the validation data. Bárdossy and Singh (2008) studied this problem for single-objective calibration problems using the example of hydrological models and proposed a geometrical sampling approach called Robust Parameter Estimation (ROPE). This approach applies the concept of data depth in order to overcome the shortcomings of automatic calibration procedures and find a set of robust parameter vectors. Recent studies confirmed the effectivity of this method. However, all ROPE approaches published so far just identify robust model

  12. Robust multi-objective calibration strategies – possibilities for improving flood forecasting

    Directory of Open Access Journals (Sweden)

    G. H. Schmitz

    2012-10-01

    Full Text Available Process-oriented rainfall-runoff models are designed to approximate the complex hydrologic processes within a specific catchment and in particular to simulate the discharge at the catchment outlet. Most of these models exhibit a high degree of complexity and require the determination of various parameters by calibration. Recently, automatic calibration methods became popular in order to identify parameter vectors with high corresponding model performance. The model performance is often assessed by a purpose-oriented objective function. Practical experience suggests that in many situations one single objective function cannot adequately describe the model's ability to represent any aspect of the catchment's behaviour. This is regardless of whether the objective is aggregated of several criteria that measure different (possibly opposite aspects of the system behaviour. One strategy to circumvent this problem is to define multiple objective functions and to apply a multi-objective optimisation algorithm to identify the set of Pareto optimal or non-dominated solutions. Nonetheless, there is a major disadvantage of automatic calibration procedures that understand the problem of model calibration just as the solution of an optimisation problem: due to the complex-shaped response surface, the estimated solution of the optimisation problem can result in different near-optimum parameter vectors that can lead to a very different performance on the validation data. Bárdossy and Singh (2008 studied this problem for single-objective calibration problems using the example of hydrological models and proposed a geometrical sampling approach called Robust Parameter Estimation (ROPE. This approach applies the concept of data depth in order to overcome the shortcomings of automatic calibration procedures and find a set of robust parameter vectors. Recent studies confirmed the effectivity of this method. However, all ROPE approaches published so far just identify

  13. Many-objective robust decision making for water allocation under climate change.

    Science.gov (United States)

    Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E

    2017-12-31

    Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large rivers. The framework was applied to the Pearl River basin (PRB), China where sufficient flow to the delta is required to reduce saltwater intrusion in the dry season. Before identifying and assessing robust water allocation plans for the future, the performance of ten state-of-the-art MOEAs (multi-objective evolutionary algorithms) is evaluated for the water allocation problem in the PRB. The Borg multi-objective evolutionary algorithm (Borg MOEA), which is a self-adaptive optimization algorithm, has the best performance during the historical periods. Therefore it is selected to generate new water allocation plans for the future (2079-2099). This study shows that robust decision making using carefully selected MOEAs can help limit saltwater intrusion in the Pearl River Delta. However, the framework could perform poorly due to larger than expected climate change impacts on water availability. Results also show that subjective design choices from the researchers and/or water managers could potentially affect the ability of the model framework, and cause the most robust water allocation plans to fail under future climate change. Developing robust allocation plans in a river basin suffering from increasing water shortage requires the researchers and water managers to well characterize future climate change of the study regions and vulnerabilities of their tools. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. A data set for evaluating the performance of multi-class multi-object video tracking

    Science.gov (United States)

    Chakraborty, Avishek; Stamatescu, Victor; Wong, Sebastien C.; Wigley, Grant; Kearney, David

    2017-05-01

    One of the challenges in evaluating multi-object video detection, tracking and classification systems is having publically available data sets with which to compare different systems. However, the measures of performance for tracking and classification are different. Data sets that are suitable for evaluating tracking systems may not be appropriate for classification. Tracking video data sets typically only have ground truth track IDs, while classification video data sets only have ground truth class-label IDs. The former identifies the same object over multiple frames, while the latter identifies the type of object in individual frames. This paper describes an advancement of the ground truth meta-data for the DARPA Neovision2 Tower data set to allow both the evaluation of tracking and classification. The ground truth data sets presented in this paper contain unique object IDs across 5 different classes of object (Car, Bus, Truck, Person, Cyclist) for 24 videos of 871 image frames each. In addition to the object IDs and class labels, the ground truth data also contains the original bounding box coordinates together with new bounding boxes in instances where un-annotated objects were present. The unique IDs are maintained during occlusions between multiple objects or when objects re-enter the field of view. This will provide: a solid foundation for evaluating the performance of multi-object tracking of different types of objects, a straightforward comparison of tracking system performance using the standard Multi Object Tracking (MOT) framework, and classification performance using the Neovision2 metrics. These data have been hosted publically.

  15. Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

    Science.gov (United States)

    Kwakkel, Jan; Haasnoot, Marjolijn

    2017-04-01

    Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

  16. A Novel SHLNN Based Robust Control and Tracking Method for Hypersonic Vehicle under Parameter Uncertainty

    Directory of Open Access Journals (Sweden)

    Chuanfeng Li

    2017-01-01

    Full Text Available Hypersonic vehicle is a typical parameter uncertain system with significant characteristics of strong coupling, nonlinearity, and external disturbance. In this paper, a combined system modeling approach is proposed to approximate the actual vehicle system. The state feedback control strategy is adopted based on the robust guaranteed cost control (RGCC theory, where the Lyapunov function is applied to get control law for nonlinear system and the problem is transformed into a feasible solution by linear matrix inequalities (LMI method. In addition, a nonfragile guaranteed cost controller solved by LMI optimization approach is employed to the linear error system, where a single hidden layer neural network (SHLNN is employed as an additive gain compensator to reduce excessive performance caused by perturbations and uncertainties. Simulation results show the stability and well tracking performance for the proposed strategy in controlling the vehicle system.

  17. Infants Track Word Forms in Early Word-Object Associations

    Science.gov (United States)

    Zamuner, Tania S.; Fais, Laurel; Werker, Janet F.

    2014-01-01

    A central component of language development is word learning. One characterization of this process is that language learners discover objects and then look for word forms to associate with these objects (Mcnamara, 1984; Smith, 2000). Another possibility is that word forms themselves are also important, such that once learned, hearing a familiar…

  18. Tracking Students' Eye-Movements When Reading Learning Objects on Mobile Phones: A Discourse Analysis of Luganda Language Teacher-Trainees' Reflective Observations

    Science.gov (United States)

    Kabugo, David; Muyinda, Paul B.; Masagazi, Fred. M.; Mugagga, Anthony M.; Mulumba, Mathias B.

    2016-01-01

    Although eye-tracking technologies such as Tobii-T120/TX and Eye-Tribe are steadily becoming ubiquitous, and while their appropriation in education can aid teachers to collect robust information on how students move their eyes when reading and engaging with different learning objects, many teachers of Luganda language are yet to gain experiences…

  19. Correlation and 3D-tracking of objects by pointing sensors

    Science.gov (United States)

    Griesmeyer, J. Michael

    2017-04-04

    A method and system for tracking at least one object using a plurality of pointing sensors and a tracking system are disclosed herein. In a general embodiment, the tracking system is configured to receive a series of observation data relative to the at least one object over a time base for each of the plurality of pointing sensors. The observation data may include sensor position data, pointing vector data and observation error data. The tracking system may further determine a triangulation point using a magnitude of a shortest line connecting a line of sight value from each of the series of observation data from each of the plurality of sensors to the at least one object, and perform correlation processing on the observation data and triangulation point to determine if at least two of the plurality of sensors are tracking the same object. Observation data may also be branched, associated and pruned using new incoming observation data.

  20. Robust Adaptive Fuzzy Design for Ship Linear-tracking Control with Input Saturation

    Directory of Open Access Journals (Sweden)

    Yancai Hu

    2017-04-01

    Full Text Available A robust adaptive control approach is proposed for underactuated surface ship linear path-tracking control system based on the backstepping control method and Lyapunov stability theory. By employing T-S fuzzy system to approximate nonlinear uncertainties of the control system, the proposed scheme is developed by combining “dynamic surface control” (DSC and “minimal learning parameter” (MLP techniques. The substantial problems of “explosion of complexity” and “dimension curse” existed in the traditional backstepping technique are circumvented, and it is convenient to implement in applications. In addition, an auxiliary system is developed to deal with the effect of input saturation constraints. The control algorithm avoids the singularity problem of controller and guarantees the stability of the closed-loop system. The tracking error converges to an arbitrarily small neighborhood. Finally, MATLAB simulation results are given from an application case of Dalian Maritime University training ship to demonstrate the effectiveness of the proposed scheme.

  1. A Computer Vision Approach to Object Tracking and Counting

    Directory of Open Access Journals (Sweden)

    Sergiu Mezei

    2010-09-01

    Full Text Available This paper, introduces a new method for counting people or more generally objects that enter or exit a certain area/building or perimeter. We propose an algorithm (method that analyzes a video sequence, detects moving objects and their moving direction and filters them according to some criteria (ex only humans. As result one obtains in and out counters for objects passing the defined perimeter. Automatic object counting is a growing size application in many industry/commerce areas. Counting can be used in statistical analysis and optimal activity scheduling methods. One of the main applications is the approximation of the number of persons passing trough, or reaching a certain area: airports (customs, shopping centers and malls and sports or cultural activities with high attendance. The main purpose is to offer an accurate estimation while still keeping the anonymity of the visitors.

  2. Robust Takagi-Sugeno Fuzzy Dynamic Regulator for Trajectory Tracking of a Pendulum-Cart System

    Directory of Open Access Journals (Sweden)

    Miguel A. Llama

    2015-01-01

    Full Text Available Starting from a nonlinear model for a pendulum-cart system, on which viscous friction is considered, a Takagi-Sugeno (T-S fuzzy augmented model (TSFAM as well as a TSFAM with uncertainty (TSFAMwU is proposed. Since the design of a T-S fuzzy controller is based on the T-S fuzzy model of the nonlinear system, then, to address the trajectory tracking problem of the pendulum-cart system, three T-S fuzzy controllers are proposed via parallel distributed compensation: (1 a T-S fuzzy servo controller (TSFSC designed from the TSFAM; (2 a robust TSFSC (RTSFSC designed from the TSFAMwU; and (3 a robust T-S fuzzy dynamic regulator (RTSFDR designed from the RTSFSC with the addition of a T-S fuzzy observer, which estimates cart and pendulum velocities. Both TSFAM and TSFAMwU are comprised of two fuzzy rules and designed via local approximation in fuzzy partition spaces technique. Feedback gains for the three fuzzy controllers are obtained via linear matrix inequalities approach. A swing-up controller is developed to swing the pendulum up from its pendant position to its upright position. Real-time experiments validate the effectiveness of the proposed schemes, keeping the pendulum in its upright position while the cart follows a reference signal, standing out the RTSFDR.

  3. A Robust Tracking Control System Design for Autonomous Underwater Vehicles Based on Sliding Mode Control

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Seung Yun [Agency for Defense Development (Korea, Republic of); Lee, Man Hyung [Pusan National University (Korea, Republic of)

    1998-02-01

    In this paper, a robust path tracking and diving control system of Autonomous Underwater Vehicle based on sliding mode control is presented. We have also d signed augmented equivalent control inputs by analyzing the sliding mode with the reaching mode. This can enhance the reaching rate, and improve chattering problems, that is, noise caused by the control plane actuator of the vehicle, which is one of the problems that occur when sliding mode control is used. Also to resolve the steady state error generated in the path tracker under current effect, a modified sliding plane is constructed. Also a redesigned sliding plane and control input using transformation matrix is proposed to do easy design of MIMO depth controller. For state variables that cannot be measured directly, reduced order sliding mode control is used to design an observer. The performance of designed path tracker and depth controller is investigated by computer simulation. The results show that the proposed control system has robust performance to parameter variation, modelling error and disturbance. (author). 12 refs., 14 figs., 1 tab.

  4. Tracking Location and Features of Objects within Visual Working Memory

    Directory of Open Access Journals (Sweden)

    Michael Patterson

    2012-10-01

    Full Text Available Four studies examined how color or shape features can be accessed to retrieve the memory of an object's location. In each trial, 6 colored dots (Experiments 1 and 2 or 6 black shapes (Experiments 3 and 4 were displayed in randomly selected locations for 1.5 s. An auditory cue for either the shape or the color to-be-remembered was presented either simultaneously, immediately, or 2 s later. Non-informative cues appeared in some trials to serve as a control condition. After a 4 s delay, 5/6 objects were re-presented, and participants indicated the location of the missing object either by moving the mouse (Experiments 1 and 3, or by typing coordinates using a grid (Experiments 2 and 4. Compared to the control condition, cues presented simultaneously or immediately after stimuli improved location accuracy in all experiments. However, cues presented after 2 s only improved accuracy in Experiment 1. These results suggest that location information may not be addressable within visual working memory using shape features. In Experiment 1, but not Experiments 2–4, cues significantly improved accuracy when they indicated the missing object could be any of the three identical objects. In Experiments 2–4, location accuracy was highly impaired when the missing object came from a group of identical rather than uniquely identifiable objects. This indicates that when items with similar features are presented, location accuracy may be reduced. In summary, both feature type and response mode can influence the accuracy and accessibility of visual working memory for object location.

  5. Bi-objective robust optimization of machined surface quality and productivity under vibrations limitation

    Directory of Open Access Journals (Sweden)

    Sahali M.A.

    2015-01-01

    Full Text Available In this contribution, a bi-objective robust optimization of cutting parameters, with the taking into account uncertainties inherent in the tool wear and the tool deflection for a turning operation is presented. In a first step, we proceed to the construction of substitution models that connect the cutting parameters to the variables of interest based on design of experiments. Our two objectives are the best machined surface quality and the maximum productivity under consideration of limitations related to the vibrations and the range of the three cutting parameters. Then, using the developed genetic algorithm that based on a robust evaluation mechanism of chromosomes by Monte-Carlo simulations, the influence and interest of the uncertainties integration in the machining optimization is demonstrated. After comparing the classical and robust Pareto fronts, A surface quality less efficient but robust can be obtained with the consideration of uncontrollable factors or uncertainties unlike that provides the deterministic and classical optimization for the same values of productivity.

  6. Towards a Stable Robotic Object Manipulation Through 2D-3D Features Tracking

    Directory of Open Access Journals (Sweden)

    Sorin M. Grigorescu

    2013-04-01

    Full Text Available In this paper, a new object tracking system is proposed to improve the object manipulation capabilities of service robots. The goal is to continuously track the state of the visualized environment in order to send visual information in real time to the path planning and decision modules of the robot; that is, to adapt the movement of the robotic system according to the state variations appearing in the imaged scene. The tracking approach is based on a probabilistic collaborative tracking framework developed around a 2D patch-based tracking system and a 2D-3D point features tracker. The real-time visual information is composed of RGB-D data streams acquired from state-of-the-art structured light sensors. For performance evaluation, the accuracy of the developed tracker is compared to a traditional marker-based tracking system which delivers 3D information with respect to the position of the marker.

  7. Real-time object tracking for moving target auto-focus in digital camera

    Science.gov (United States)

    Guan, Haike; Niinami, Norikatsu; Liu, Tong

    2015-02-01

    Focusing at a moving object accurately is difficult and important to take photo of the target successfully in a digital camera. Because the object often moves randomly and changes its shape frequently, position and distance of the target should be estimated at real-time so as to focus at the objet precisely. We propose a new method of real-time object tracking to do auto-focus for moving target in digital camera. Video stream in the camera is used for the moving target tracking. Particle filter is used to deal with problem of the target object's random movement and shape change. Color and edge features are used as measurement of the object's states. Parallel processing algorithm is developed to realize real-time particle filter object tracking easily in hardware environment of the digital camera. Movement prediction algorithm is also proposed to remove focus error caused by difference between tracking result and target object's real position when the photo is taken. Simulation and experiment results in digital camera demonstrate effectiveness of the proposed method. We embedded real-time object tracking algorithm in the digital camera. Position and distance of the moving target is obtained accurately by object tracking from the video stream. SIMD processor is applied to enforce parallel real-time processing. Processing time less than 60ms for each frame is obtained in the digital camera with its CPU of only 162MHz.

  8. Robust Multi-Objective PQ Scheduling for Electric Vehicles in Flexible Unbalanced Distribution Grids

    DEFF Research Database (Denmark)

    Knezovic, Katarina; Soroudi, Alireza; Marinelli, Mattia

    2017-01-01

    . The robust formulation effectively considers the errors in the electricity price forecast and its influence on the EV schedule. Moreover, the impact of EV reactive power support on objective values and technical parameters is analysed both when EVs are the only flexible resources and when linked with other......With increased penetration of distributed energy resources and electric vehicles (EVs), different EV management strategies can be used for mitigating adverse effects and supporting the distribution grid. This paper proposes a robust multi-objective methodology for determining the optimal day...... demand response programs. The method is tested on a real Danish unbalanced distribution grid with 35% EV penetration to demonstrate the effectiveness of the proposed approach. It is shown that the proposed formulation guarantees an optimal EV cost as long as the price uncertainties are lower than...

  9. 3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

    Science.gov (United States)

    Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

    2017-10-01

    Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.

  10. Robustness

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Rizzuto, Enrico; Narasimhan, Harikrishna

    2012-01-01

    More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of structures...

  11. Many-objective robust decision making for managing an ecosystem with a deeply uncertain threshold response

    Directory of Open Access Journals (Sweden)

    Riddhi Singh

    2015-09-01

    Full Text Available Managing ecosystems with deeply uncertain threshold responses and multiple decision makers poses nontrivial decision analytical challenges. The problem is imbued with deep uncertainties because decision makers do not know or cannot converge on a single probability density function for each key parameter, a perfect model structure, or a single adequate objective. The existing literature on managing multistate ecosystems has generally followed a normative decision-making approach based on expected utility maximization (MEU. This approach has simple and intuitive axiomatic foundations, but faces at least two limitations. First, a prespecified utility function is often unable to capture the preferences of diverse decision makers. Second, decision makers' preferences depart from MEU in the presence of deep uncertainty. Here, we introduce a framework that allows decision makers to pose multiple objectives, explore the trade-offs between potentially conflicting preferences of diverse decision makers, and to identify strategies that are robust to deep uncertainties. The framework, referred to as many-objective robust decision making (MORDM, employs multiobjective evolutionary search to identify trade-offs between strategies, re-evaluates their performance under deep uncertainty, and uses interactive visual analytics to support the selection of robust management strategies. We demonstrate MORDM on a stylized decision problem posed by the management of a lake in which surpassing a pollution threshold causes eutrophication. Our results illustrate how framing the lake problem in terms of MEU can fail to represent key trade-offs between phosphorus levels in the lake and expected economic benefits. Moreover, the MEU strategy deteriorates severely in performance for all objectives under deep uncertainties. Alternatively, the MORDM framework enables the discovery of strategies that balance multiple preferences and perform well under deep uncertainty. This

  12. A Robust and Efficient Curve Skeletonization Algorithm for Tree-Like Objects Using Minimum Cost Paths

    OpenAIRE

    Jin, Dakai; Iyer, Krishna S; Chen, Cheng; Hoffman, Eric A; Saha, Punam K

    2015-01-01

    Conventional curve skeletonization algorithms using the principle of Blum���s transform, often, produce unwanted spurious branches due to boundary irregularities, digital effects, and other artifacts. This paper presents a new robust and efficient curve skeletonization algorithm for three-dimensional (3-D) elongated fuzzy objects using a minimum cost path approach, which avoids spurious branches without requiring post-pruning. Starting from a root voxel, the method iteratively expands the ske...

  13. A Single Unexpected Change in Target- but Not Distractor Motion Impairs Multiple Object Tracking

    Directory of Open Access Journals (Sweden)

    Hauke S. Meyerhoff

    2013-02-01

    Full Text Available Recent research addresses the question whether motion information of multiple objects contributes to maintaining a selection of objects across a period of motion. Here, we investigate whether target and/or distractor motion information is used during attentive tracking. We asked participants to track four objects and changed either the motion direction of targets, the motion direction of distractors, neither, or both during a brief flash in the middle of a tracking interval. We observed that a single direction change of targets is sufficient to impair tracking performance. In contrast, changing the motion direction of distractors had no effect on performance. This indicates that target- but not distractor motion information is evaluated during tracking.

  14. Behavioral dynamics and neural grounding of a dynamic field theory of multi-object tracking.

    Science.gov (United States)

    Spencer, J P; Barich, K; Goldberg, J; Perone, S

    2012-09-01

    The ability to dynamically track moving objects in the environment is crucial for efficient interaction with the local surrounds. Here, we examined this ability in the context of the multi-object tracking (MOT) task. Several theories have been proposed to explain how people track moving objects; however, only one of these previous theories is implemented in a real-time process model, and there has been no direct contact between theories of object tracking and the growing neural literature using ERPs and fMRI. Here, we present a neural process model of object tracking that builds from a Dynamic Field Theory of spatial cognition. Simulations reveal that our dynamic field model captures recent behavioral data examining the impact of speed and tracking duration on MOT performance. Moreover, we show that the same model with the same trajectories and parameters can shed light on recent ERP results probing how people distribute attentional resources to targets vs. distractors. We conclude by comparing this new theory of object tracking to other recent accounts, and discuss how the neural grounding of the theory might be effectively explored in future work.

  15. Joint estimation fusion and tracking of objects in a single camera using EM-EKF

    Science.gov (United States)

    Sathyaraj. S, Pristley; Leung, Henry

    2013-09-01

    Tracking objects in dynamic scene is an interesting area of research and it has it's applications in many areas like surveillance, missile tracking system,virtual reality and robot vision. Objects in real world exhibit complex interactions with each other. When captured in a video signal, these interactions manifest themselves as in- tertwineing motions , occlusion and pose changes. A video tracking system should track these objects in this complex interactions smoothly . This paper presents a new joint method for tracking moving objects in outdoor and indoor environment. This joint method uses recursive Expectation-Maximization (EM) incorporated with Extended Kalman Filter (EKF) to estimate, fuse and track the object simultaneously, than doing it in two dif- ferent steps. This combined approach provides more realistic solution to the problem. Thereby, outperforming the conventional method of treating it as three di erent problems. We have tested our algorithm with standard dataset and real time video sequences collected from indoor environment. We also nd that the usage of the joint method improves the accuracy and computational cost. This method successfully tracks object with occlusions, di erent orientations and intertwining motion.

  16. Neutrosophic Similarity Score Based Weighted Histogram for Robust Mean-Shift Tracking

    Directory of Open Access Journals (Sweden)

    Keli Hu

    2017-10-01

    Full Text Available Visual object tracking is a critical task in computer vision. Challenging things always exist when an object needs to be tracked. For instance, background clutter is one of the most challenging problems. The mean-shift tracker is quite popular because of its efficiency and performance in a range of conditions. However, the challenge of background clutter also disturbs its performance. In this article, we propose a novel weighted histogram based on neutrosophic similarity score to help the mean-shift tracker discriminate the target from the background. Neutrosophic set (NS is a new branch of philosophy for dealing with incomplete, indeterminate, and inconsistent information. In this paper, we utilize the single valued neutrosophic set (SVNS, which is a subclass of NS to improve the mean-shift tracker. First, two kinds of criteria are considered as the object feature similarity and the background feature similarity, and each bin of the weight histogram is represented in the SVNS domain via three membership functions T(Truth, I(indeterminacy, and F(Falsity. Second, the neutrosophic similarity score function is introduced to fuse those two criteria and to build the final weight histogram. Finally, a novel neutrosophic weighted mean-shift tracker is proposed. The proposed tracker is compared with several mean-shift based trackers on a dataset of 61 public sequences. The results revealed that our method outperforms other trackers, especially when confronting background clutter.

  17. An Adaptive Object Tracking Using Kalman Filter and Probability Product Kernel

    Directory of Open Access Journals (Sweden)

    Hamd Ait Abdelali

    2016-01-01

    Full Text Available We present a new method for object tracking; we use an efficient local search scheme based on the Kalman filter and the probability product kernel (KFPPK to find the image region with a histogram most similar to the histogram of the tracked target. Experimental results verify the effectiveness of this proposed system.

  18. Tracking Student Achievement in Music Performance: Developing Student Learning Objectives for Growth Model Assessments

    Science.gov (United States)

    Wesolowski, Brian C.

    2015-01-01

    Student achievement growth data are increasingly used for assessing teacher effectiveness and tracking student achievement in the classroom. Guided by the student learning objective (SLO) framework, music teachers are now responsible for collecting, tracking, and reporting student growth data. Often, the reported data do not accurately reflect the…

  19. Object detection via eye tracking and fringe restraint

    Science.gov (United States)

    Pan, Fei; Zhang, Hanming; Zeng, Ying; Tong, Li; Yan, Bin

    2017-07-01

    Object detection is a computer vision problem which caught a large amount of attention. But the candidate boundingboxes extracted from only image features may end up with false-detection due to the semantic gap between the top-down and the bottom up information. In this paper, we propose a novel method for generating object bounding-boxes proposals using the combination of eye fixation point, saliency detection and edges. The new method obtains a fixation orientated Gaussian map, optimizes the map through single-layer cellular automata, and derives bounding-boxes from the optimized map on three levels. Then we score the boxes by combining all the information above, and choose the box with the highest score to be the final box. We perform an evaluation of our method by comparing with previous state-ofthe art approaches on the challenging POET datasets, the images of which are chosen from PASCAL VOC 2012. Our method outperforms them on small scale objects while comparable to them in general.

  20. Fast region-based object detection and tracking using correlation of features

    CSIR Research Space (South Africa)

    Senekal, F

    2010-11-01

    Full Text Available typically have certain visual characteristics and where the environmental variables such as lighting and camera position can be controlled as well. In the work conducted here, a method is sought that can be applied in arbitrary situations.... In such situations, there may be considerable variation in the visual characteristics of the object that should be tracked and in the environmental conditions. In a general situation, the object that should be tracked might have variations in the colour...

  1. Long-term microfluidic tracking of coccoid cyanobacterial cells reveals robust control of division timing.

    Science.gov (United States)

    Yu, Feiqiao Brian; Willis, Lisa; Chau, Rosanna Man Wah; Zambon, Alessandro; Horowitz, Mark; Bhaya, Devaki; Huang, Kerwyn Casey; Quake, Stephen R

    2017-02-14

    Cyanobacteria are important agents in global carbon and nitrogen cycling and hold great promise for biotechnological applications. Model organisms such as Synechocystis sp. and Synechococcus sp. have advanced our understanding of photosynthetic capacity and circadian behavior, mostly using population-level measurements in which the behavior of individuals cannot be monitored. Synechocystis sp. cells are small and divide slowly, requiring long-term experiments to track single cells. Thus, the cumulative effects of drift over long periods can cause difficulties in monitoring and quantifying cell growth and division dynamics. To overcome this challenge, we enhanced a microfluidic cell-culture device and developed an image analysis pipeline for robust lineage reconstruction. This allowed simultaneous tracking of many cells over multiple generations, and revealed that cells expand exponentially throughout their cell cycle. Generation times were highly correlated for sister cells, but not between mother and daughter cells. Relationships between birth size, division size, and generation time indicated that cell-size control was inconsistent with the "sizer" rule, where division timing is based on cell size, or the "timer" rule, where division occurs after a fixed time interval. Instead, single cell growth statistics were most consistent with the "adder" rule, in which division occurs after a constant increment in cell volume. Cells exposed to light-dark cycles exhibited growth and division only during the light period; dark phases pause but do not disrupt cell-cycle control. Our analyses revealed that the "adder" model can explain both the growth-related statistics of single Synechocystis cells and the correlation between sister cell generation times. We also observed rapid phenotypic response to light-dark transitions at the single cell level, highlighting the critical role of light in cyanobacterial cell-cycle control. Our findings suggest that by monitoring the growth

  2. Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

    Directory of Open Access Journals (Sweden)

    Lei Qin

    2014-05-01

    Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

  3. Detection and tracking of dynamic objects by using a multirobot system: application to critical infrastructures surveillance.

    Science.gov (United States)

    Rodríguez-Canosa, Gonzalo; del Cerro Giner, Jaime; Cruz, Antonio Barrientos

    2014-02-12

    The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed.

  4. Finding Robust Adaptation Gene Regulatory Networks Using Multi-Objective Genetic Algorithm.

    Science.gov (United States)

    Ren, Hai-Peng; Huang, Xiao-Na; Hao, Jia-Xuan

    2016-01-01

    Robust adaptation plays a key role in gene regulatory networks, and it is thought to be an important attribute for the organic or cells to survive in fluctuating conditions. In this paper, a simplified three-node enzyme network is modeled by the Michaelis-Menten rate equations for all possible topologies, and a family of topologies and the corresponding parameter sets of the network with satisfactory adaptation are obtained using the multi-objective genetic algorithm. The proposed approach improves the computation efficiency significantly as compared to the time consuming exhaustive searching method. This approach provides a systemic way for searching the feasible topologies and the corresponding parameter sets to make the gene regulatory networks have robust adaptation. The proposed methodology, owing to its universality and simplicity, can be used to address more complex issues in biological networks.

  5. Development of Robust Behaviour Recognition for an at-Home Biomonitoring Robot with Assistance of Subject Localization and Enhanced Visual Tracking

    Directory of Open Access Journals (Sweden)

    Nevrez Imamoglu

    2014-01-01

    Full Text Available Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy.

  6. Generalized Extended State Observer Approach to Robust Tracking Control for Wheeled Mobile Robot with Skidding and Slipping

    Directory of Open Access Journals (Sweden)

    Hyo-Seok Kang

    2013-03-01

    Full Text Available This paper proposes a robust tracking controller based on a Generalized Extended State Observer (GESO method for a wheeled mobile robot (WMR with unknown skidding and slipping. Skidding and slipping of a WMR are inevitable in practice. We regard skidding and slipping as disturbances and modify the dynamics model to consider them simply. Then, we adopt the GESO to design a robust tracking controller at kinematic and dynamic level. Using Lyapunov theory, we derive the control law and guarantee the stability of the control system. The proposed control achieves attenuation of the disturbance and convergence of the tracking errors. The performance of the proposed method is verified by some simulation results.

  7. Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

    Science.gov (United States)

    Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

    2017-05-01

    Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

  8. Multi-frequency GNSS robust carrier tracking for ionospheric scintillation mitigation

    Science.gov (United States)

    Vilà-Valls, Jordi; Closas, Pau; Curran, James T.

    2017-10-01

    Ionospheric scintillation is the physical phenomena affecting radio waves propagating from the space through the ionosphere to earth. The signal distortion induced by scintillation can pose a major threat to some GNSS application. Scintillation is one of the more challenging propagation scenarios, particularly affecting high-precision GNSS receivers which require high quality carrier phase measurements; and safety critical applications which have strict accuracy, availability and integrity requirements. Under ionospheric scintillation conditions, GNSS signals are affected by fast amplitude and phase variations, which can compromise the receiver synchronization. To take into account the underlying correlation among different frequency bands, we propose a new multivariate autoregressive model (MAR) for the multi-frequency ionospheric scintillation process. Multi-frequency GNSS observations and the scintillation MAR are modeled in state-space, allowing independent tracking of both line-of-sight phase variations and complex gain scintillation components. The resulting joint synchronization and scintillation mitigation problem is solved using a robust nonlinear Kalman filter, validated using real multi-frequency scintillation data with encouraging results.

  9. Tracking the global jet streams through objective analysis

    Science.gov (United States)

    Gallego, D.; Peña-Ortiz, C.; Ribera, P.

    2009-12-01

    Although the tropospheric jet streams are probably the more important single dynamical systems in the troposphere, their study at climatic scale has been usually troubled by the difficulty of characterising their structure. During the last years, a deal of effort has been made in order to construct long-term scale objective climatologies of the jet stream or at least to understand the variability of the westerly flux in the upper troposphere. A main problem with studying the jets is the necessity of using highly derivated fields as the potential vorticity or even the analysis of chemical tracers. Despite their utility, these approaches are very problematic to construct an automatic searching algorithm because of the difficulty of defining criteria for these extremely noisy fields. Some attempts have been addressed trying to use only the wind field to find the jet. This direct approach avoids the use of derivate variables, but it must contain some stringent criteria to filter the large number of tropospheric wind maxima not related to the jet currents. This approach has offered interesting results for the relatively simple structure of the Southern Hemisphere tropospheric jets (Gallego et al. Clim. Dyn, 2005). However, the much more complicated structure of its northern counterpart has resisted the analysis with the same degree of detail by using the wind alone. In this work we present a new methodology able to characterise the position, strength and altitude of the jet stream at global scale on a daily basis. The method is based on the analysis of the 3-D wind field alone and it searches, at each longitude, relative wind maxima in the upper troposphere between the levels of 400 and 100 hPa. An ad-hoc defined density function (dependent on the season and the longitude) of the detection positions is used as criteria to filter spurious wind maxima not related to the jet. The algorithm has been applied to the NCEP/NCAR reanalysis and the results show that the basic

  10. The Dynamic Model Embed in Augmented Graph Cuts for Robust Hand Tracking and Segmentation in Videos

    Directory of Open Access Journals (Sweden)

    Jun Wan

    2014-01-01

    Full Text Available Segmenting human hand is important in computer vision applications, for example, sign language interpretation, human computer interaction, and gesture recognition. However, some serious bottlenecks still exist in hand localization systems such as fast hand motion capture, hand over face, and hand occlusions on which we focus in this paper. We present a novel method for hand tracking and segmentation based on augmented graph cuts and dynamic model. First, an effective dynamic model for state estimation is generated, which correctly predicts the location of hands probably having fast motion or shape deformations. Second, new energy terms are brought into the energy function to develop augmented graph cuts based on some cues, namely, spatial information, hand motion, and chamfer distance. The proposed method successfully achieves hand segmentation even though the hand passes over other skin-colored objects. Some challenging videos are provided in the case of hand over face, hand occlusions, dynamic background, and fast motion. Experimental results demonstrate that the proposed method is much more accurate than other graph cuts-based methods for hand tracking and segmentation.

  11. Ground-based Tracking of Geosynchronous Space Objects with a GM-CPHD Filter

    Science.gov (United States)

    Jones, B.; Hatten, N.; Ravago, N.; Russell, R.

    2016-09-01

    This paper presents a multi-target tracker for space objects near geosynchronous orbit using the Gaussian Mixture Cardinalized Probability Hypothesis Density (CPHD) filter. Given limited sensor coverage and more than 1,000 objects near geosynchronous orbit, long times between measurement updates for a single object can yield propagated uncertainties sufficiently large to create ambiguities in observation-to-track association. Recent research considers various methods for tracking space objects via Bayesian multi-target filters, with the CPHD being one such example. The implementation of the CPHD filter presented in this paper includes models consistent with the space-object tracking problem to form a new space-object tracker. This tracker combines parallelization with efficient models and integrators to reduce the run time of Gaussian-component propagation. To allow for instantiating new objects, the proposed filter uses a variation of the probabilistic admissible region that adheres to assumptions in the derivation of the CPHD filter. Finally, to reduce computation time while mitigating the so-called "spooky action at a distance" phenomenon in the CPHD filter, we propose splitting the multi-target state into distinct, non-interacting populations based on the sensor's field of view. In a scenario with 700 near-geosynchronous objects observed via three ground stations, the tracker maintains custody of initially known objects and instantiates tracks for newly detected ones. The mean filter estimation after a 48 hour observation campaign is comparable to the measurement error statistics.

  12. Tuning rules for robust FOPID controllers based on multi-objective optimization with FOPDT models.

    Science.gov (United States)

    Sánchez, Helem Sabina; Padula, Fabrizio; Visioli, Antonio; Vilanova, Ramon

    2017-01-01

    In this paper a set of optimally balanced tuning rules for fractional-order proportional-integral-derivative controllers is proposed. The control problem of minimizing at once the integrated absolute error for both the set-point and the load disturbance responses is addressed. The control problem is stated as a multi-objective optimization problem where a first-order-plus-dead-time process model subject to a robustness, maximum sensitivity based, constraint has been considered. A set of Pareto optimal solutions is obtained for different normalized dead times and then the optimal balance between the competing objectives is obtained by choosing the Nash solution among the Pareto-optimal ones. A curve fitting procedure has then been applied in order to generate suitable tuning rules. Several simulation results show the effectiveness of the proposed approach. Copyright © 2016. Published by Elsevier Ltd.

  13. An efficient Lagrangean relaxation-based object tracking algorithm in wireless sensor networks.

    Science.gov (United States)

    Lin, Frank Yeong-Sung; Lee, Cheng-Ta

    2010-01-01

    In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs). Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given frequencies for each pair of sensor nodes and link transmission cost. This problem is formulated as a 0/1 integer-programming problem. A Lagrangean relaxation-based (LR-based) heuristic algorithm is proposed for solving the optimization problem. Experimental results showed that the proposed algorithm achieves near optimization in energy-efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time.

  14. Anisotropic versus isotropic distribution of attention in object tracking: Disentangling influences of overt and covert attention

    NARCIS (Netherlands)

    Frielink-Loing, A.F.; Koning, A.R.; Lier, R.J. van

    2015-01-01

    In recent studies, multiple-object tracking (MOT) tasks combined with probe detection tasks have been used to investigate the distribution of attention around moving objects (e.g., Atsma, Koning & van Lier, 2012). During these tasks, participants were allowed to move their eyes freely around the

  15. A Robust and Efficient Curve Skeletonization Algorithm for Tree-Like Objects Using Minimum Cost Paths.

    Science.gov (United States)

    Jin, Dakai; Iyer, Krishna S; Chen, Cheng; Hoffman, Eric A; Saha, Punam K

    2016-06-01

    Conventional curve skeletonization algorithms using the principle of Blum's transform, often, produce unwanted spurious branches due to boundary irregularities, digital effects, and other artifacts. This paper presents a new robust and efficient curve skeletonization algorithm for three-dimensional (3-D) elongated fuzzy objects using a minimum cost path approach, which avoids spurious branches without requiring post-pruning. Starting from a root voxel, the method iteratively expands the skeleton by adding new branches in each iteration that connects the farthest quench voxel to the current skeleton using a minimum cost path. The path-cost function is formulated using a novel measure of local significance factor defined by the fuzzy distance transform field, which forces the path to stick to the centerline of an object. The algorithm terminates when dilated skeletal branches fill the entire object volume or the current farthest quench voxel fails to generate a meaningful skeletal branch. Accuracy of the algorithm has been evaluated using computer-generated phantoms with known skeletons. Performance of the method in terms of false and missing skeletal branches, as defined by human experts, has been examined using in vivo CT imaging of human intrathoracic airways. Results from both experiments have established the superiority of the new method as compared to the existing methods in terms of accuracy as well as robustness in detecting true and false skeletal branches. The new algorithm makes a significant reduction in computation complexity by enabling detection of multiple new skeletal branches in one iteration. Specifically, this algorithm reduces the number of iterations from the number of terminal tree branches to the worst case performance of tree depth. In fact, experimental results suggest that, on an average, the order of computation complexity is reduced to the logarithm of the number of terminal branches of a tree-like object.

  16. 3D Shape-Encoded Particle Filter for Object Tracking and Its Application to Human Body Tracking

    Directory of Open Access Journals (Sweden)

    R. Chellappa

    2008-03-01

    Full Text Available We present a nonlinear state estimation approach using particle filters, for tracking objects whose approximate 3D shapes are known. The unnormalized conditional density for the solution to the nonlinear filtering problem leads to the Zakai equation, and is realized by the weights of the particles. The weight of a particle represents its geometric and temporal fit, which is computed bottom-up from the raw image using a shape-encoded filter. The main contribution of the paper is the design of smoothing filters for feature extraction combined with the adoption of unnormalized conditional density weights. The “shape filter” has the overall form of the predicted 2D projection of the 3D model, while the cross-section of the filter is designed to collect the gradient responses along the shape. The 3D-model-based representation is designed to emphasize the changes in 2D object shape due to motion, while de-emphasizing the variations due to lighting and other imaging conditions. We have found that the set of sparse measurements using a relatively small number of particles is able to approximate the high-dimensional state distribution very effectively. As a measures to stabilize the tracking, the amount of random diffusion is effectively adjusted using a Kalman updating of the covariance matrix. For a complex problem of human body tracking, we have successfully employed constraints derived from joint angles and walking motion.

  17. 3D Shape-Encoded Particle Filter for Object Tracking and Its Application to Human Body Tracking

    Directory of Open Access Journals (Sweden)

    Chellappa R

    2008-01-01

    Full Text Available Abstract We present a nonlinear state estimation approach using particle filters, for tracking objects whose approximate 3D shapes are known. The unnormalized conditional density for the solution to the nonlinear filtering problem leads to the Zakai equation, and is realized by the weights of the particles. The weight of a particle represents its geometric and temporal fit, which is computed bottom-up from the raw image using a shape-encoded filter. The main contribution of the paper is the design of smoothing filters for feature extraction combined with the adoption of unnormalized conditional density weights. The "shape filter" has the overall form of the predicted 2D projection of the 3D model, while the cross-section of the filter is designed to collect the gradient responses along the shape. The 3D-model-based representation is designed to emphasize the changes in 2D object shape due to motion, while de-emphasizing the variations due to lighting and other imaging conditions. We have found that the set of sparse measurements using a relatively small number of particles is able to approximate the high-dimensional state distribution very effectively. As a measures to stabilize the tracking, the amount of random diffusion is effectively adjusted using a Kalman updating of the covariance matrix. For a complex problem of human body tracking, we have successfully employed constraints derived from joint angles and walking motion.

  18. Comparing dogs and great apes in their ability to visually track object transpositions.

    Science.gov (United States)

    Rooijakkers, Eveline F; Kaminski, Juliane; Call, Josep

    2009-11-01

    Knowing that objects continue to exist after disappearing from sight and tracking invisible object displacements are two basic elements of spatial cognition. The current study compares dogs and apes in an invisible transposition task. Food was hidden under one of two cups in full view of the subject. After that both cups were displaced, systematically varying two main factors, whether cups were crossed during displacement and whether the cups were substituted by the other cup or instead cups were moved to new locations. While the apes were successful in all conditions, the dogs had a strong preference to approach the location where they last saw the reward, especially if this location remained filled. In addition, dogs seem to have special difficulties to track the reward when both containers crossed their path during displacement. These results confirm the substantial difference that exists between great apes and dogs with regard to mental representation abilities required to track the invisible displacements of objects.

  19. Tracking of multiple objects with time-adjustable composite correlation filters

    Science.gov (United States)

    Ruchay, Alexey; Kober, Vitaly; Chernoskulov, Ilya

    2017-09-01

    An algorithm for tracking of multiple objects in video based on time-adjustable adaptive composite correlation filtering is proposed. For each frame a bank of composite correlation filters are designed in such a manner to provide invariance to pose, occlusion, clutter, and illumination changes. The filters are synthesized with the help of an iterative algorithm, which optimizes the discrimination capability for each object. The filters are adapted to the objects changes online using information from the current and past scene frames. Results obtained with the proposed algorithm using real-life scenes are presented and compared with those obtained with state-of-the-art tracking methods in terms of detection efficiency, tracking accuracy, and speed of processing.

  20. A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking.

    Directory of Open Access Journals (Sweden)

    Mohammad Javad Shafiee

    Full Text Available In this work, we introduce a deep-structured conditional random field (DS-CRF model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering.

  1. Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

    Science.gov (United States)

    Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

    2018-01-01

    Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

  2. A Mobility-Aware Adaptive Duty Cycling Mechanism for Tracking Objects during Tunnel Excavation.

    Science.gov (United States)

    Kim, Taesik; Min, Hong; Jung, Jinman

    2017-02-23

    Tunnel construction workers face many dangers while working under dark conditions, with difficult access and egress, and many potential hazards. To enhance safety at tunnel construction sites, low latency tracking of mobile objects (e.g., heavy-duty equipment) and construction workers is critical for managing the dangerous construction environment. Wireless Sensor Networks (WSNs) are the basis for a widely used technology for monitoring the environment because of their energy-efficiency and scalability. However, their use involves an inherent point-to-point delay caused by duty cycling mechanisms that can result in a significant rise in the delivery latency for tracking mobile objects. To overcome this issue, we proposed a mobility-aware adaptive duty cycling mechanism for the WSNs based on object mobility. For the evaluation, we tested this mechanism for mobile object tracking at a tunnel excavation site. The evaluation results showed that the proposed mechanism could track mobile objects with low latency while they were moving, and could reduce energy consumption by increasing sleep time while the objects were immobile.

  3. A Mobility-Aware Adaptive Duty Cycling Mechanism for Tracking Objects during Tunnel Excavation

    Directory of Open Access Journals (Sweden)

    Taesik Kim

    2017-02-01

    Full Text Available Tunnel construction workers face many dangers while working under dark conditions, with difficult access and egress, and many potential hazards. To enhance safety at tunnel construction sites, low latency tracking of mobile objects (e.g., heavy-duty equipment and construction workers is critical for managing the dangerous construction environment. Wireless Sensor Networks (WSNs are the basis for a widely used technology for monitoring the environment because of their energy-efficiency and scalability. However, their use involves an inherent point-to-point delay caused by duty cycling mechanisms that can result in a significant rise in the delivery latency for tracking mobile objects. To overcome this issue, we proposed a mobility-aware adaptive duty cycling mechanism for the WSNs based on object mobility. For the evaluation, we tested this mechanism for mobile object tracking at a tunnel excavation site. The evaluation results showed that the proposed mechanism could track mobile objects with low latency while they were moving, and could reduce energy consumption by increasing sleep time while the objects were immobile.

  4. Many-Objective Robust Decision Making: Managing Water in a Deeply Uncertain World of Change (Invited)

    Science.gov (United States)

    Reed, P. M.

    2013-12-01

    Water resources planning and management has always required the consideration of uncertainties and the associated system vulnerabilities that they may cause. Despite the long legacy of these issues, our decision support frameworks that have dominated the literature over the past 50 years have struggled with the strongly multiobjective and deeply uncertain nature of water resources systems. The term deep uncertainty (or Knightian uncertainty) refers to factors in planning that strongly shape system risks that maybe unknown and even if known there is a strong lack of consensus on their likelihoods over decadal planning horizons (population growth, financial stability, valuation of resources, ecosystem requirements, evolving water institutions, regulations, etc). In this presentation, I will propose and demonstrate the many-objective robust decision making (MORDM) framework for water resources management under deep uncertainty. The MORDM framework will be demonstrated using an urban water portfolio management test case. In the test case, a city in the Lower Rio Grande Valley managing population and drought pressures must cost effectively maintain the reliability of its water supply by blending permanent rights to reservoir inflows with alternative strategies for purchasing water within the region's water market. The case study illustrates the significant potential pitfalls in the classic Cost-Reliability conception of the problem. Moreover, the proposed MORDM framework exploits recent advances in multiobjective search, visualization, and sensitivity analysis to better expose these pitfalls en route to identifying highly robust water planning alternatives.

  5. Moving Object Tracking and Its Application to an Indoor Dual-Robot Patrol

    Directory of Open Access Journals (Sweden)

    Cheng-Han Shih

    2016-11-01

    Full Text Available This paper presents an application of image tracking using an omnidirectional wheeled mobile robot (WMR. The objective of this study is to integrate image processing of hue, saturation, and lightness (HSL for fuzzy color space, and use mean shift tracking for object detection and a Radio Frequency Identification (RFID reader for confirming destination. Fuzzy control is applied to omnidirectional WMR for indoor patrol and intruder detection. Experimental results show that the proposed control scheme can make the WMRs perform indoor security service.

  6. IMPLEMENTATION OF IMAGE PROCESSING ALGORITHMS AND GLVQ TO TRACK AN OBJECT USING AR.DRONE CAMERA

    Directory of Open Access Journals (Sweden)

    Muhammad Nanda Kurniawan

    2014-08-01

    Full Text Available Abstract In this research, Parrot AR.Drone as an Unmanned Aerial Vehicle (UAV was used to track an object from above. Development of this system utilized some functions from OpenCV library and Robot Operating System (ROS. Techniques that were implemented in the system are image processing al-gorithm (Centroid-Contour Distance (CCD, feature extraction algorithm (Principal Component Analysis (PCA and an artificial neural network algorithm (Generalized Learning Vector Quantization (GLVQ. The final result of this research is a program for AR.Drone to track a moving object on the floor in fast response time that is under 1 second.

  7. Optimized UAV object tracking framework based on Integrated Particle filter with ego-motion transformation matrix

    Directory of Open Access Journals (Sweden)

    Askar Wesam

    2017-01-01

    Full Text Available Vision based object tracking problem still a hot and important area of research specially when the tracking algorithms are performed by the aircraft unmanned vehicle (UAV. Tracking with the UAV requires special considerations due to the flight maneuvers, environmental conditions and aircraft moving camera. The ego motion calculations can compensate the effect of the moving background resulted from the moving camera. In this paper an optimized object tracking framework is introduced to tackle this problem based on particle filter. It integrates the calculated ego motion transformation matrix with the dynamic model of the particle filter during the prediction stage. Then apply the correction stage on the particle filter observation model which based on two kinds of features includes Haar-like Rectangles and edge orientation histogram (EOH features. The Gentle AdaBoost classifier is used to select the most informative features as a preliminary step. The experimental results achieved more than 94.6% rate of successful tracking during different scenarios of the VIVID database in real time tracking speed.

  8. Adaptive Position/Attitude Tracking Control of Aerial Robot With Unknown Inertial Matrix Based on a New Robust Neural Identifier.

    Science.gov (United States)

    Lai, Guanyu; Liu, Zhi; Zhang, Yun; Chen, C L Philip

    2016-01-01

    This paper presents a novel adaptive controller for controlling an autonomous helicopter with unknown inertial matrix to asymptotically track the desired trajectory. To identify the unknown inertial matrix included in the attitude dynamic model, this paper proposes a new structural identifier that differs from those previously proposed in that it additionally contains a neural networks (NNs) mechanism and a robust adaptive mechanism, respectively. Using the NNs to compensate the unknown aerodynamic forces online and the robust adaptive mechanism to cancel the combination of the overlarge NNs compensation error and the external disturbances, the new robust neural identifier exhibits a better identification performance in the complex flight environment. Moreover, an optimized algorithm is included in the NNs mechanism to alleviate the burdensome online computation. By the strict Lyapunov argument, the asymptotic convergence of the inertial matrix identification error, position tracking error, and attitude tracking error to arbitrarily small neighborhood of the origin is proved. The simulation and implementation results are provided to evaluate the performance of the proposed controller.

  9. Robust Tracking Control of Robot Manipulators Using Only Joint Position Measurements

    Directory of Open Access Journals (Sweden)

    Ancai Zhang

    2013-01-01

    Full Text Available This paper concerns the tracking control of a robot manipulator with unknown uncertainties and disturbances. It presents a new control method that uses only joint position measurements to design a tracking controller. The controller has two parts. One is based on a feedback linearization technique; it makes the nominal model of a manipulator asymptotically track a desired trajectory. The other is based on the idea of equivalent input disturbance (EID; it compensates for uncertainties and disturbances. Together they enable a robot manipulator to precisely track the desired trajectory. The new control algorithm is applied to a two-link robot manipulator, and simulation results demonstrate the validity of this method.

  10. Investigation of the robustness of adaptive neuro-fuzzy inference system for tracking moving tumors in external radiotherapy.

    Science.gov (United States)

    Torshabi, Ahmad Esmaili

    2014-12-01

    In external radiotherapy of dynamic targets such as lung and breast cancers, accurate correlation models are utilized to extract real time tumor position by means of external surrogates in correlation with the internal motion of tumors. In this study, a correlation method based on the neuro-fuzzy model is proposed to correlate the input external motion data with internal tumor motion estimation in real-time mode, due to its robustness in motion tracking. An initial test of the performance of this model was reported in our previous studies. In this work by implementing some modifications it is resulted that ANFIS is still robust to track tumor motion more reliably by reducing the motion estimation error remarkably. After configuring new version of our ANFIS model, its performance was retrospectively tested over ten patients treated with Synchrony Cyberknife system. In order to assess the performance of our model, the predicted tumor motion as model output was compared with respect to the state of the art model. Final analyzed results show that our adaptive neuro-fuzzy model can reduce tumor tracking errors more significantly, as compared with ground truth database and even tumor tracking methods presented in our previous works.

  11. A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Bahadır KARASULU

    2013-04-01

    Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

  12. Spatio-temporal patterns of brain activity distinguish strategies of multiple-object tracking.

    Science.gov (United States)

    Merkel, Christian; Stoppel, Christian M; Hillyard, Steven A; Heinze, Hans-Jochen; Hopf, Jens-Max; Schoenfeld, Mircea Ariel

    2014-01-01

    Human observers can readily track up to four independently moving items simultaneously, even in the presence of moving distractors. Here we combined EEG and magnetoencephalography recordings to investigate the neural processes underlying this remarkable capability. Participants were instructed to track four of eight independently moving items for 3 sec. When the movement ceased a probe stimulus consisting of four items with a higher luminance was presented. The location of the probe items could correspond fully, partly, or not at all with the tracked items. Participants reported whether the probe items fully matched the tracked items or not. About half of the participants showed slower RTs and higher error rates with increasing correspondence between tracked items and the probe. The other half, however, showed faster RTs and lower error rates when the probe fully matched the tracked items. This latter behavioral pattern was associated with enhanced probe-evoked neural activity that was localized to the lateral occipital cortex in the time range 170-210 msec. This enhanced response in the object-selective lateral occipital cortex suggested that these participants performed the tracking task by visualizing the overall shape configuration defined by the vertices of the tracked items, thereby producing a behavioral advantage on full-match trials. In a later time range (270-310 msec) probe-evoked neural activity increased monotonically as a function of decreasing target-probe correspondence in all participants. This later modulation, localized to superior parietal cortex, was proposed to reflect the degree of mismatch between the probe and the automatically formed visual STM representation of the tracked items.

  13. AUTONOMOUS DETECTION AND TRACKING OF AN OBJECT AUTONOMOUSLY USING AR.DRONE QUADCOPTER

    Directory of Open Access Journals (Sweden)

    Futuhal Arifin

    2014-08-01

    Full Text Available Abstract Nowadays, there are many robotic applications being developed to do tasks autonomously without any interactions or commands from human. Therefore, developing a system which enables a robot to do surveillance such as detection and tracking of a moving object will lead us to more advanced tasks carried out by robots in the future. AR.Drone is a flying robot platform that is able to take role as UAV (Unmanned Aerial Vehicle. Usage of computer vision algorithm such as Hough Transform makes it possible for such system to be implemented on AR.Drone. In this research, the developed algorithm is able to detect and track an object with certain shape and color. Then the algorithm is successfully implemented on AR.Drone quadcopter for detection and tracking.

  14. Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects

    Science.gov (United States)

    Prasad, Narasimha S.; Rudd, Van; Shald, Scott; Sandford, Stephen; Dimarcantonio, Albert

    2014-01-01

    In this paper, the development of a long range ladar system known as ExoSPEAR at NASA Langley Research Center for tracking rapidly moving resident space objects is discussed. Based on 100 W, nanosecond class, near-IR laser, this ladar system with coherent detection technique is currently being investigated for short dwell time measurements of resident space objects (RSOs) in LEO and beyond for space surveillance applications. This unique ladar architecture is configured using a continuously agile doublet-pulse waveform scheme coupled to a closed-loop tracking and control loop approach to simultaneously achieve mm class range precision and mm/s velocity precision and hence obtain unprecedented track accuracies. Salient features of the design architecture followed by performance modeling and engagement simulations illustrating the dependence of range and velocity precision in LEO orbits on ladar parameters are presented. Estimated limits on detectable optical cross sections of RSOs in LEO orbits are discussed.

  15. Object Tracking with LiDAR: Monitoring Taxiing and Landing Aircraft

    Directory of Open Access Journals (Sweden)

    Zoltan Koppanyi

    2018-02-01

    Full Text Available Mobile light detection and ranging (LiDAR sensors used in car navigation and robotics, such as the Velodyne’s VLP-16 and HDL-32E, allow for sensing the surroundings of the platform with high temporal resolution to detect obstacles, tracking objects and support path planning. This study investigates the feasibility of using LiDAR sensors for tracking taxiing or landing aircraft close to the ground to improve airport safety. A prototype system was developed and installed at an airfield to capture point clouds to monitor aircraft operations. One of the challenges of accurate object tracking using the Velodyne sensors is the relatively small vertical field of view (30°, 41.3° and angular resolution (1.33°, 2°, resulting in a small number of points of the tracked object. The point density decreases with the object–sensor distance, and is already sparse at a moderate range of 30–40 m. The paper introduces our model-based tracking algorithms, including volume minimization and cube trajectories, to address the optimal estimation of object motion and tracking based on sparse point clouds. Using a network of sensors, multiple tests were conducted at an airport to assess the performance of the demonstration system and the algorithms developed. The investigation was focused on monitoring small aircraft moving on runways and taxiways, and the results indicate less than 0.7 m/s and 17 cm velocity and positioning accuracy achieved, respectively. Overall, based on our findings, this technology is promising not only for aircraft monitoring but for airport applications.

  16. Algorithm of search and track of static and moving large-scale objects

    Directory of Open Access Journals (Sweden)

    Kalyaev Anatoly

    2017-01-01

    Full Text Available We suggest an algorithm for processing of a sequence, which contains images of search and track of static and moving large-scale objects. The possible software implementation of the algorithm, based on multithread CUDA processing, is suggested. Experimental analysis of the suggested algorithm implementation is performed.

  17. Real-time tracking of visually attended objects in virtual environments and its application to LOD.

    Science.gov (United States)

    Lee, Sungkil; Kim, Gerard Jounghyun; Choi, Seungmoon

    2009-01-01

    This paper presents a real-time framework for computationally tracking objects visually attended by the user while navigating in interactive virtual environments. In addition to the conventional bottom-up (stimulus-driven) saliency map, the proposed framework uses top-down (goal-directed) contexts inferred from the user's spatial and temporal behaviors, and identifies the most plausibly attended objects among candidates in the object saliency map. The computational framework was implemented using GPU, exhibiting high computational performance adequate for interactive virtual environments. A user experiment was also conducted to evaluate the prediction accuracy of the tracking framework by comparing objects regarded as visually attended by the framework to actual human gaze collected with an eye tracker. The results indicated that the accuracy was in the level well supported by the theory of human cognition for visually identifying single and multiple attentive targets, especially owing to the addition of top-down contextual information. Finally, we demonstrate how the visual attention tracking framework can be applied to managing the level of details in virtual environments, without any hardware for head or eye tracking.

  18. Techniques for efficient road-network-based tracking of moving objects

    DEFF Research Database (Denmark)

    Civilis, A.; Jensen, Christian Søndergaard; Pakalnis, Stardas

    2005-01-01

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects...

  19. Techniques for Efficient Tracking of Road-Network-Based Moving Objects

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian Søndergaard; Saltenis, Simonas

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects...

  20. Pupil Sizes Scale with Attentional Load and Task Experience in a Multiple Object Tracking Task

    OpenAIRE

    Wahn, Basil; FERRIS, DANIEL P.; Hairston, W. David; K?nig, Peter

    2016-01-01

    Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted...

  1. Ego-Motion and Tracking for Continuous Object Learning: A Brief Survey

    Science.gov (United States)

    2017-09-01

    timation and object tracking fields. We believe these capabilities are required to support online adaptive learning of objects in dynamic environments . This...dense 3d modeling of indoor environments . The International Journal of Robotics Research. 2012;31(5):647–663. Approved for public release...Institute of Technology; 2013. 43. Tipaldi GD, Meyer-Delius D, Burgard W. Lifelong localization in changing environments . The International Journal of

  2. Development of an FPGA Based Embedded System for High Speed Object Tracking

    Directory of Open Access Journals (Sweden)

    Chandrashekar MATHAM

    2010-01-01

    Full Text Available This paper deals with the development and implementation of system on chip (SOC for object tracking using histograms. To acquire the distance and velocity information of moving vehicles such as military tanks, to identify the type of target within the range from 100 m to 3 km and to estimate the movements of the vehicle. The VHDL code is written for the above objectives and implemented using Xilinx’s VERTEX-4 based PCI card family.

  3. Cross-Modal Attention Effects in the Vestibular Cortex during Attentive Tracking of Moving Objects.

    Science.gov (United States)

    Frank, Sebastian M; Sun, Liwei; Forster, Lisa; Tse, Peter U; Greenlee, Mark W

    2016-12-14

    The midposterior fundus of the Sylvian fissure in the human brain is central to the cortical processing of vestibular cues. At least two vestibular areas are located at this site: the parietoinsular vestibular cortex (PIVC) and the posterior insular cortex (PIC). It is now well established that activity in sensory systems is subject to cross-modal attention effects. Attending to a stimulus in one sensory modality enhances activity in the corresponding cortical sensory system, but simultaneously suppresses activity in other sensory systems. Here, we wanted to probe whether such cross-modal attention effects also target the vestibular system. To this end, we used a visual multiple-object tracking task. By parametrically varying the number of tracked targets, we could measure the effect of attentional load on the PIVC and the PIC while holding the perceptual load constant. Participants performed the tracking task during functional magnetic resonance imaging. Results show that, compared with passive viewing of object motion, activity during object tracking was suppressed in the PIVC and enhanced in the PIC. Greater attentional load, induced by increasing the number of tracked targets, was associated with a corresponding increase in the suppression of activity in the PIVC. Activity in the anterior part of the PIC decreased with increasing load, whereas load effects were absent in the posterior PIC. Results of a control experiment show that attention-induced suppression in the PIVC is stronger than any suppression evoked by the visual stimulus per se. Overall, our results suggest that attention has a cross-modal modulatory effect on the vestibular cortex during visual object tracking. In this study we investigate cross-modal attention effects in the human vestibular cortex. We applied the visual multiple-object tracking task because it is known to evoke attentional load effects on neural activity in visual motion-processing and attention-processing areas. Here we

  4. Tracking of maneuvering non-ellipsoidal extended target with varying number of sub-objects

    Science.gov (United States)

    Hu, Qi; Ji, Hongbing; Zhang, Yongquan

    2018-01-01

    A target that generates multiple measurements at each time step is called the extended target and an ellipse can be used to approximate its extension. When the spatial distributions of measurements can reflect its true shape, in this situation the extended target is called a non-ellipsoidal extended target and its complicated extended state cannot be accurately approximated by single ellipse. In view of this, the non-ellipsoidal extended target tracking (NETT) filter was proposed, which uses multiple ellipses (called sub-objects) to approximate the extended state. However, the existing NETT filters are limited to the framework that the number of sub-objects remains still, which does not match the actual tracking situations. When the attitude of the target changes, the view from the sensor on the target may change, then the shape of the non-ellipsoidal extended target varies as well as the reasonable number of sub-objects needed for approximation. To solve this problem, we propose a varying number of sub-objects for non-ellipsoidal extended target tracking gamma Gaussian inverse Wishart (VN-NETT-GGIW) filter. The proposed filter estimates the kinematic, extension and measurement-rate states of each sub-object as well as the number of sub-objects. The simulation results show that the proposed filter can be used for the target changing attitude situation and is more close to the practice application.

  5. Multisensory Tracking of Objects in Darkness: Capture of Positive Afterimages by the Tactile and Proprioceptive Senses.

    Directory of Open Access Journals (Sweden)

    Brian W Stone

    Full Text Available This paper reports on three experiments investigating the contribution of different sensory modalities to the tracking of objects moved in total darkness. Participants sitting in the dark were exposed to a brief, bright flash which reliably induced a positive visual afterimage of the scene so illuminated. If the participants subsequently move their hand in the darkness, the visual afterimage of that hand fades or disappears; this is presumably due to conflict between the illusory visual afterimage (of the hand in its original location and other information (e.g., proprioceptive from a general mechanism for tracking body parts. This afterimage disappearance effect also occurs for held objects which are moved in the dark, and some have argued that this represents a case of body schema extension, i.e. the rapid incorporation of held external objects into the body schema. We demonstrate that the phenomenon is not limited to held objects and occurs in conditions where incorporation into the body schema is unlikely. Instead, we propose that the disappearance of afterimages of objects moved in darkness comes from a general mechanism for object tracking which integrates input from multiple sensory systems. This mechanism need not be limited to tracking body parts, and thus we need not invoke body schema extension to explain the afterimage disappearance. In this series of experiments, we test whether auditory feedback of object movement can induce afterimage disappearance, demonstrate that the disappearance effect scales with the magnitude of proprioceptive feedback, and show that tactile feedback alone is sufficient for the effect. Together, these data demonstrate that the visual percept of a positive afterimage is constructed not just from visual input of the scene when light reaches the eyes, but in conjunction with input from multiple other senses.

  6. Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

    Directory of Open Access Journals (Sweden)

    Zhijun Xie

    2014-10-01

    Full Text Available Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT. In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

  7. Multiple object tracking in molecular bioimaging by Rao-Blackwellized marginal particle filtering.

    Science.gov (United States)

    Smal, I; Meijering, E; Draegestein, K; Galjart, N; Grigoriev, I; Akhmanova, A; van Royen, M E; Houtsmuller, A B; Niessen, W

    2008-12-01

    Time-lapse fluorescence microscopy imaging has rapidly evolved in the past decade and has opened new avenues for studying intracellular processes in vivo. Such studies generate vast amounts of noisy image data that cannot be analyzed efficiently and reliably by means of manual processing. Many popular tracking techniques exist but often fail to yield satisfactory results in the case of high object densities, high noise levels, and complex motion patterns. Probabilistic tracking algorithms, based on Bayesian estimation, have recently been shown to offer several improvements over classical approaches, by better integration of spatial and temporal information, and the possibility to more effectively incorporate prior knowledge about object dynamics and image formation. In this paper, we extend our previous work in this area and propose an improved, fully automated particle filtering algorithm for the tracking of many subresolution objects in fluorescence microscopy image sequences. It involves a new track management procedure and allows the use of multiple dynamics models. The accuracy and reliability of the algorithm are further improved by applying marginalization concepts. Experiments on synthetic as well as real image data from three different biological applications clearly demonstrate the superiority of the algorithm compared to previous particle filtering solutions.

  8. Robust FDI for A Ship-mounted Satellite Tracking Antenna: A Nonlinear Approach

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal

    2008-01-01

    Overseas telecommunication is preserved by means of satellite communication. Tracking system postures the on-board antenna toward a chosen satellite while the external disturbances affect the antenna. Certain faults (beam sensor malfunction or signal blocking) cause interruption in the communicat......Overseas telecommunication is preserved by means of satellite communication. Tracking system postures the on-board antenna toward a chosen satellite while the external disturbances affect the antenna. Certain faults (beam sensor malfunction or signal blocking) cause interruption...... in the communication connection resulting in the loss of the tracking functionality. In this paper, an optimization based fault diagnosis system is proposed for the nonlinear model of the satellite tracking antenna (STA). The suggested method is able to estimate the fault for a class of nonlinear systems acting under...

  9. Solving advanced multi-objective robust designs by means of multiple objective evolutionary algorithms (MOEA): A reliability application

    Energy Technology Data Exchange (ETDEWEB)

    Salazar A, Daniel E. [Division de Computacion Evolutiva (CEANI), Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria (IUSIANI), Universidad de Las Palmas de Gran Canaria. Canary Islands (Spain)]. E-mail: danielsalazaraponte@gmail.com; Rocco S, Claudio M. [Universidad Central de Venezuela, Facultad de Ingenieria, Caracas (Venezuela)]. E-mail: crocco@reacciun.ve

    2007-06-15

    This paper extends the approach proposed by the second author in [Rocco et al. Robust design using a hybrid-cellular-evolutionary and interval-arithmetic approach: a reliability application. In: Tarantola S, Saltelli A, editors. SAMO 2001: Methodological advances and useful applications of sensitivity analysis. Reliab Eng Syst Saf 2003;79(2):149-59 [special issue

  10. Using LabView for real-time monitoring and tracking of multiple biological objects

    Science.gov (United States)

    Nikolskyy, Aleksandr I.; Krasilenko, Vladimir G.; Bilynsky, Yosyp Y.; Starovier, Anzhelika

    2017-04-01

    Today real-time studying and tracking of movement dynamics of various biological objects is important and widely researched. Features of objects, conditions of their visualization and model parameters strongly influence the choice of optimal methods and algorithms for a specific task. Therefore, to automate the processes of adaptation of recognition tracking algorithms, several Labview project trackers are considered in the article. Projects allow changing templates for training and retraining the system quickly. They adapt to the speed of objects and statistical characteristics of noise in images. New functions of comparison of images or their features, descriptors and pre-processing methods will be discussed. The experiments carried out to test the trackers on real video files will be presented and analyzed.

  11. Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

    Science.gov (United States)

    Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

    2015-11-01

    Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

  12. Online Object Tracking, Learning and Parsing with And-Or Graphs.

    Science.gov (United States)

    Wu, Tianfu; Lu, Yang; Zhu, Song-Chun

    2017-12-01

    This paper presents a method, called AOGTracker, for simultaneously tracking, learning and parsing (TLP) of unknown objects in video sequences with a hierarchical and compositional And-Or graph (AOG) representation. The TLP method is formulated in the Bayesian framework with a spatial and a temporal dynamic programming (DP) algorithms inferring object bounding boxes on-the-fly. During online learning, the AOG is discriminatively learned using latent SVM [1] to account for appearance (e.g., lighting and partial occlusion) and structural (e.g., different poses and viewpoints) variations of a tracked object, as well as distractors (e.g., similar objects) in background. Three key issues in online inference and learning are addressed: (i) maintaining purity of positive and negative examples collected online, (ii) controling model complexity in latent structure learning, and (iii) identifying critical moments to re-learn the structure of AOG based on its intrackability. The intrackability measures uncertainty of an AOG based on its score maps in a frame. In experiments, our AOGTracker is tested on two popular tracking benchmarks with the same parameter setting: the TB-100/50/CVPR2013 benchmarks  , [3] , and the VOT benchmarks [4] -VOT 2013, 2014, 2015 and TIR2015 (thermal imagery tracking). In the former, our AOGTracker outperforms state-of-the-art tracking algorithms including two trackers based on deep convolutional network   [5] , [6] . In the latter, our AOGTracker outperforms all other trackers in VOT2013 and is comparable to the state-of-the-art methods in VOT2014, 2015 and TIR2015.

  13. Robust detection and tracking of annotations for outdoor augmented reality browsing

    Science.gov (United States)

    Langlotz, Tobias; Degendorfer, Claus; Mulloni, Alessandro; Schall, Gerhard; Reitmayr, Gerhard; Schmalstieg, Dieter

    2011-01-01

    A common goal of outdoor augmented reality (AR) is the presentation of annotations that are registered to anchor points in the real world. We present an enhanced approach for registering and tracking such anchor points, which is suitable for current generation mobile phones and can also successfully deal with the wide variety of viewing conditions encountered in real life outdoor use. The approach is based on on-the-fly generation of panoramic images by sweeping the camera over the scene. The panoramas are then used for stable orientation tracking, while the user is performing only rotational movements. This basic approach is improved by several new techniques for the re-detection and tracking of anchor points. For the re-detection, specifically after temporal variations, we first compute a panoramic image with extended dynamic range, which can better represent varying illumination conditions. The panorama is then searched for known anchor points, while orientation tracking continues uninterrupted. We then use information from an internal orientation sensor to prime an active search scheme for the anchor points, which improves matching results. Finally, global consistency is enhanced by statistical estimation of a global rotation that minimizes the overall position error of anchor points when transforming them from the source panorama in which they were created, to the current view represented by a new panorama. Once the anchor points are redetected, we track the user's movement using a novel 3-degree-of-freedom orientation tracking approach that combines vision tracking with the absolute orientation from inertial and magnetic sensors. We tested our system using an AR campus guide as an example application and provide detailed results for our approach using an off-the-shelf smartphone. Results show that the re-detection rate is improved by a factor of 2 compared to previous work and reaches almost 90% for a wide variety of test cases while still keeping the ability

  14. Young infants' visual fixation patterns in addition and subtraction tasks support an object tracking account.

    Science.gov (United States)

    Bremner, J Gavin; Slater, Alan M; Hayes, Rachel A; Mason, Uschi C; Murphy, Caroline; Spring, Jo; Draper, Lucinda; Gaskell, David; Johnson, Scott P

    2017-10-01

    Investigating infants' numerical ability is crucial to identifying the developmental origins of numeracy. Wynn (1992) claimed that 5-month-old infants understand addition and subtraction as indicated by longer looking at outcomes that violate numerical operations (i.e., 1+1=1 and 2-1=2). However, Wynn's claim was contentious, with others suggesting that her results might reflect a familiarity preference for the initial array or that they could be explained in terms of object tracking. To cast light on this controversy, Wynn's conditions were replicated with conventional looking time supplemented with eye-tracker data. In the incorrect outcome of 2 in a subtraction event (2-1=2), infants looked selectively at the incorrectly present object, a finding that is not predicted by an initial array preference account or a symbolic numerical account but that is consistent with a perceptual object tracking account. It appears that young infants can track at least one object over occlusion, and this may form the precursor of numerical ability. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  15. A New Distance Measure Based on Generalized Image Normalized Cross-Correlation for Robust Video Tracking and Image Recognition.

    Science.gov (United States)

    Nakhmani, Arie; Tannenbaum, Allen

    2013-02-01

    We propose two novel distance measures, normalized between 0 and 1, and based on normalized cross-correlation for image matching. These distance measures explicitly utilize the fact that for natural images there is a high correlation between spatially close pixels. Image matching is used in various computer vision tasks, and the requirements to the distance measure are application dependent. Image recognition applications require more shift and rotation robust measures. In contrast, registration and tracking applications require better localization and noise tolerance. In this paper, we explore different advantages of our distance measures, and compare them to other popular measures, including Normalized Cross-Correlation (NCC) and Image Euclidean Distance (IMED). We show which of the proposed measures is more appropriate for tracking, and which is appropriate for image recognition tasks.

  16. Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity

    Directory of Open Access Journals (Sweden)

    Hyuncheol Kim

    2014-01-01

    Full Text Available We address object tracking problem as a multitask feature learning process based on low-rank representation of features with joint sparsity. We first select features with low-rank representation within a number of initial frames to obtain subspace basis. Next, the features represented by the low-rank and sparse property are learned using a modified joint sparsity-based multitask feature learning framework. Both the features and sparse errors are then optimally updated using a novel incremental alternating direction method. The low-rank minimization problem for learning multitask features can be achieved by a few sequences of efficient closed form update process. Since the proposed method attempts to perform the feature learning problem in both multitask and low-rank manner, it can not only reduce the dimension but also improve the tracking performance without drift. Experimental results demonstrate that the proposed method outperforms existing state-of-the-art tracking methods for tracking objects in challenging image sequences.

  17. Robust H(infinity) tracking control of boiler-turbine systems.

    Science.gov (United States)

    Wu, J; Nguang, S K; Shen, J; Liu, G; Li, Y G

    2010-07-01

    In this paper, the problem of designing a fuzzy H(infinity) state feedback tracking control of a boiler-turbine is solved. First, the Takagi and Sugeno fuzzy model is used to model a boiler-turbine system. Next, based on the Takagi and Sugeno fuzzy model, sufficient conditions for the existence of a fuzzy H(infinity) nonlinear state feedback tracking control are derived in terms of linear matrix inequalities. The advantage of the proposed tracking control design is that it does not involve feedback linearization technique and complicated adaptive scheme. An industrial boiler-turbine system is used to illustrate the effectiveness of the proposed design as compared with a linearized approach. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Robust formation tracking control of mobile robots via one-to-one time-varying communication

    Science.gov (United States)

    Dasdemir, Janset; Loría, Antonio

    2014-09-01

    We solve the formation tracking control problem for mobile robots via linear control, under the assumption that each agent communicates only with one 'leader' robot and with one follower, hence forming a spanning-tree topology. We assume that the communication may be interrupted on intervals of time. As in the classical tracking control problem for non-holonomic systems, the swarm is driven by a fictitious robot which moves about freely and which is a leader to one robot only. Our control approach is decentralised and the control laws are linear with time-varying gains; in particular, this accounts for the case when position measurements may be lost over intervals of time. For both velocity-controlled and force-controlled systems, we establish uniform global exponential stability, hence consensus formation tracking, for the error system under a condition of persistency of excitation on the reference angular velocity of the virtual leader and on the control gains.

  19. Object tracking for a class of dynamic image-based representations

    Science.gov (United States)

    Gan, Zhi-Feng; Chan, Shing-Chow; Ng, King-To; Shum, Heung-Yeung

    2005-07-01

    Image-based rendering (IBR) is an emerging technology for photo-realistic rendering of scenes from a collection of densely sampled images and videos. Recently, an object-based approach for rendering and the compression of a class of dynamic image-based representations called plenoptic videos was proposed. The plenoptic video is a simplified dynamic light field, which is obtained by capturing videos at regularly locations along a series of line segments. In the object-based approach, objects at large depth differences are segmented into layers for rendering and compression. The rendering quality in large environment can be significantly improved, as demonstrated by the pop-up lightfields. In addition, by coding the plenoptic video at the object level, desirable functionalities such as scalability of contents, error resilience, and interactivity with individual IBR objects, can be achieved. An important step in the object-based approach is to segment the objects in the video streams into layers or image-based objects, which is largely done by semi-automatic technique. To reduce the segmentation time for segmenting plenoptic videos, efficient tracking techniques are highly desirable. This paper proposes a new automatic object tracking method based on the level-set method. Our method, which utilizes both local and global features of the image sequences instead of global features exploited in previous approach, can achieve better tracking results for objects, especially with non-uniform energy distribution. Due to possible segmentation errors around object boundaries, natural matting with Bayesian approach is also incorporated into our system. Using the alpha map and texture so estimated, it is very convenient to composite the image-based objects onto the background of the original or other plenoptic videos. Furthermore, a MPEG-4 like object-based algorithm is developed for compressing the plenoptic videos, which consist of the alpha maps, depth maps and textures of the

  20. Multiple object, three-dimensional motion tracking using the Xbox Kinect sensor

    Science.gov (United States)

    Rosi, T.; Onorato, P.; Oss, S.

    2017-11-01

    In this article we discuss the capability of the Xbox Kinect sensor to acquire three-dimensional motion data of multiple objects. Two experiments regarding fundamental features of Newtonian mechanics are performed to test the tracking abilities of our setup. Particular attention is paid to check and visualise the conservation of linear momentum, angular momentum and energy. In both experiments, two objects are tracked while falling in the gravitational field. The obtained data is visualised in a 3D virtual environment to help students understand the physics behind the performed experiments. The proposed experiments were analysed with a group of university students who are aspirant physics and mathematics teachers. Their comments are presented in this paper.

  1. IMPLEMENTATION OF IMAGE PROCESSING ALGORITHMS AND GLVQ TO TRACK AN OBJECT USING AR.DRONE CAMERA

    OpenAIRE

    Muhammad Nanda Kurniawan; Didit Widiyanto

    2014-01-01

    Abstract In this research, Parrot AR.Drone as an Unmanned Aerial Vehicle (UAV) was used to track an object from above. Development of this system utilized some functions from OpenCV library and Robot Operating System (ROS). Techniques that were implemented in the system are image processing al-gorithm (Centroid-Contour Distance (CCD)), feature extraction algorithm (Principal Component Analysis (PCA)) and an artificial neural network algorithm (Generalized Learning Vector Quantization (GLV...

  2. Implementation of Image Processing Algorithms and Glvq to Track an Object Using Ar.drone Camera

    OpenAIRE

    Kurniawan, Muhammad Nanda; Widiyanto, Didit

    2014-01-01

    In this research, Parrot AR.Drone as an Unmanned Aerial Vehicle (UAV) was used to track an object from above. Development of this system utilized some functions from OpenCV library and Robot Operating System (ROS). Techniques that were implemented in the system are image processing al-gorithm (Centroid-Contour Distance (CCD)), feature extraction algorithm (Principal Component Analysis (PCA)) and an artificial neural network algorithm (Generalized Learning Vector Quantization (GLVQ)). The fina...

  3. A Mobility-Aware Adaptive Duty Cycling Mechanism for Tracking Objects during Tunnel Excavation

    OpenAIRE

    Taesik Kim; Hong Min; Jinman Jung

    2017-01-01

    Tunnel construction workers face many dangers while working under dark conditions, with difficult access and egress, and many potential hazards. To enhance safety at tunnel construction sites, low latency tracking of mobile objects (e.g., heavy-duty equipment) and construction workers is critical for managing the dangerous construction environment. Wireless Sensor Networks (WSNs) are the basis for a widely used technology for monitoring the environment because of their energy-efficiency and s...

  4. Need for Speed: A Benchmark for Higher Frame Rate Object Tracking

    OpenAIRE

    Galoogahi, Hamed Kiani; Fagg, Ashton; Huang, Chen; Ramanan, Deva; Lucey, Simon

    2017-01-01

    In this paper, we propose the first higher frame rate video dataset (called Need for Speed - NfS) and benchmark for visual object tracking. The dataset consists of 100 videos (380K frames) captured with now commonly available higher frame rate (240 FPS) cameras from real world scenarios. All frames are annotated with axis aligned bounding boxes and all sequences are manually labelled with nine visual attributes - such as occlusion, fast motion, background clutter, etc. Our benchmark provides ...

  5. Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects

    Science.gov (United States)

    Mandal, Saptarshi

    2016-01-01

    Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance. PMID:27725830

  6. Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects

    Directory of Open Access Journals (Sweden)

    Ziho Kang

    2016-01-01

    Full Text Available Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1 participants interrogate dynamic multielement objects that can overlap on the display and (2 visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1 developing dynamic areas of interests (AOIs in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2 introducing the concept of AOI gap tolerance (AGT that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3 finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC operations where air traffic controller specialists (ATCSs interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.

  7. Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

    Directory of Open Access Journals (Sweden)

    Rik Van de Walle

    2007-01-01

    Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4%.

  8. Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

    Directory of Open Access Journals (Sweden)

    Lerouge Sam

    2007-01-01

    Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4 .

  9. Robust adaptive fuzzy neural tracking control for a class of unknown ...

    Indian Academy of Sciences (India)

    In this paper, an adaptive fuzzy neural controller (AFNC) for a class of unknown chaotic systems is proposed. The proposed AFNC is comprised of a fuzzy neural controller and a robust controller. The fuzzy neural controller including a fuzzy neural network identifier (FNNI) is the principal controller. The FNNI is used for ...

  10. Modeling optical pattern recognition algorithms for object tracking based on nonlinear equivalent models and subtraction of frames

    Science.gov (United States)

    Krasilenko, Vladimir G.; Nikolskyy, Aleksandr I.; Lazarev, Alexander A.

    2015-12-01

    We have proposed and discussed optical pattern recognition algorithms for object tracking based on nonlinear equivalent models and subtraction of frames. Experimental results of suggested algorithms in Mathcad and LabVIEW are shown. Application of equivalent functions and difference of frames gives good results for recognition and tracking moving objects.

  11. Multiphase joint segmentation-registration and object tracking for layered images.

    Science.gov (United States)

    Chen, Ping-Feng; Krim, Hamid; Mendoza, Olga L

    2010-07-01

    In this paper we propose to jointly segment and register objects of interest in layered images. Layered imaging refers to imageries taken from different perspectives and possibly by different sensors. Registration and segmentation are therefore the two main tasks which contribute to the bottom level, data alignment, of the multisensor data fusion hierarchical structures. Most exploitations of two layered images assumed that scanners are at very high altitudes and that only one transformation ties the two images. Our data are however taken at mid-range and therefore requires segmentation to assist us examining different object regions in a divide-and-conquer fashion. Our approach is a combination of multiphase active contour method with a joint segmentation-registration technique (which we called MPJSR) carried out in a local moving window prior to a global optimization. To further address layered video sequences and tracking objects in frames, we propose a simple adaptation of optical flow calculations along the active contours in a pair of layered image sequences. The experimental results show that the whole integrated algorithm is able to delineate the objects of interest, align them for a pair of layered frames and keep track of the objects over time.

  12. Enhanced object-based tracking algorithm for convective rain storms and cells

    Science.gov (United States)

    Muñoz, Carlos; Wang, Li-Pen; Willems, Patrick

    2018-03-01

    This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.

  13. A Standard-Compliant Virtual Meeting System with Active Video Object Tracking

    Directory of Open Access Journals (Sweden)

    Chang Yao-Jen

    2002-01-01

    Full Text Available This paper presents an H.323 standard compliant virtual video conferencing system. The proposed system not only serves as a multipoint control unit (MCU for multipoint connection but also provides a gateway function between the H.323 LAN (local-area network and the H.324 WAN (wide-area network users. The proposed virtual video conferencing system provides user-friendly object compositing and manipulation features including 2D video object scaling, repositioning, rotation, and dynamic bit-allocation in a 3D virtual environment. A reliable, and accurate scheme based on background image mosaics is proposed for real-time extracting and tracking foreground video objects from the video captured with an active camera. Chroma-key insertion is used to facilitate video objects extraction and manipulation. We have implemented a prototype of the virtual conference system with an integrated graphical user interface to demonstrate the feasibility of the proposed methods.

  14. Modeling and Robust Trajectory Tracking Control for a Novel Six-Rotor Unmanned Aerial Vehicle

    OpenAIRE

    Yang, Chengshun; Yang, Zhong; Huang, Xiaoning; Li, Shaobin; Zhang, Qiang

    2013-01-01

    Modeling and trajectory tracking control of a novel six-rotor unmanned aerial vehicle (UAV) is concerned to solve problems such as smaller payload capacity and lack of both hardware redundancy and anticrosswind capability for quad-rotor. The mathematical modeling for the six-rotor UAV is developed on the basis of the Newton-Euler formalism, and a second-order sliding-mode disturbance observer (SOSMDO) is proposed to reconstruct the disturbances of the rotational dynamics. In consideration of ...

  15. Robust Battery Fuel Gauge Algorithm Development, Part 3: State of Charge Tracking

    Science.gov (United States)

    2014-10-19

    lithium ion batteries in electric drive vehicles using extended kalman filtering,” 2013. [13] A. P. Dempster, N. M. Laird, D. B. Rubin et al., “Maximum...identification,adaptive nonlinear filtering, extended Kalman filter (EKF), reducedorder filtering. REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT...Charge Tracking B. Balasingam, G. V. Avvari, B. Pattipati, K. Pattipati and Y. Bar-Shalom Dept. of Electrical and Computer Engineering, University of

  16. Robust optimization in IMPT using quadratic objective functions to account for the minimum MU constraint.

    Science.gov (United States)

    Shan, Jie; An, Yu; Bues, Martin; Schild, Steven E; Liu, Wei

    2018-01-01

    Currently, in clinical practice of intensity-modulated proton therapy (IMPT), the influence of the minimum monitor unit (MU) constraint is taken into account through postprocessing after the optimization is completed. This may degrade the plan quality and plan robustness. This study aims to mitigate the impact of the minimum MU constraint directly during the plan robust optimization. Cao et al. have demonstrated a two-stage method to account for the minimum MU constraint using linear programming without the impact of uncertainties considered. In this study, we took the minimum MU constraint into consideration using quadratic optimization and simultaneously had the impact of uncertainties considered using robust optimization. We evaluated our method using seven cancer patients with different machine settings. The new method achieved better plan quality than the conventional method. The D95% of the clinical target volume (CTV) normalized to the prescription dose was (mean [min-max]): (99.4% [99.2%-99.6%]) vs. (99.2% [98.6%-99.6%]). Plan robustness derived from these two methods was comparable. For all seven patients, the CTV dose-volume histogram band gap (narrower band gap means more robust plans) at D95% normalized to the prescription dose was (mean [min-max]): (1.5% [0.5%-4.3%]) vs. (1.2% [0.6%-3.8%]). Our new method of incorporating the minimum MU constraint directly into the plan robust optimization can produce machine-deliverable plans with better tumor coverage while maintaining high-plan robustness. © 2017 American Association of Physicists in Medicine.

  17. Object Tracking Vision System for Mapping the UCN τ Apparatus Volume

    Science.gov (United States)

    Lumb, Rowan; UCNtau Collaboration

    2016-09-01

    The UCN τ collaboration has an immediate goal to measure the lifetime of the free neutron to within 0.1%, i.e. about 1 s. The UCN τ apparatus is a magneto-gravitational ``bottle'' system. This system holds low energy, or ultracold, neutrons in the apparatus with the constraint of gravity, and keeps these low energy neutrons from interacting with the bottle via a strong 1 T surface magnetic field created by a bowl-shaped array of permanent magnets. The apparatus is wrapped with energized coils to supply a magnetic field throughout the ''bottle'' volume to prevent depolarization of the neutrons. An object-tracking stereo-vision system will be presented that precisely tracks a Hall probe and allows a mapping of the magnetic field throughout the volume of the UCN τ bottle. The stereo-vision system utilizes two cameras and open source openCV software to track an object's 3-d position in space in real time. The desired resolution is +/-1 mm resolution along each axis. The vision system is being used as part of an even larger system to map the magnetic field of the UCN τ apparatus and expose any possible systematic effects due to field cancellation or low field points which could allow neutrons to depolarize and possibly escape from the apparatus undetected. Tennessee Technological University.

  18. Disturbance observer-based L1 robust tracking control for hypersonic vehicles with T-S disturbance modeling

    Directory of Open Access Journals (Sweden)

    Yang Yi

    2016-11-01

    Full Text Available This article concerns a disturbance observer-based L1 robust anti-disturbance tracking algorithm for the longitudinal models of hypersonic flight vehicles with different kinds of unknown disturbances. On one hand, by applying T-S fuzzy models to represent those modeled disturbances, a disturbance observer relying on T-S disturbance models can be constructed to track the dynamics of exogenous disturbances. On the other hand, L1 index is introduced to analyze the attenuation performance of disturbance for those unmodeled disturbances. By utilizing the existing convex optimization algorithm, a disturbance observer-based proportional-integral-controlled input is proposed such that the stability of hypersonic flight vehicles can be ensured and the tracking error for velocity and altitude in hypersonic flight vehicle models can converge to equilibrium point. Furthermore, the satisfactory disturbance rejection and attenuation with L1 index can be obtained simultaneously. Simulation results on hypersonic flight vehicle models can reflect the feasibility and effectiveness of the proposed control algorithm.

  19. A reductionist approach to extract robust molecular markers from microarray data series - Isolating markers to track osseointegration.

    Science.gov (United States)

    Barik, Anwesha; Banerjee, Satarupa; Dhara, Santanu; Chakravorty, Nishant

    2017-04-01

    Complexities in the full genome expression studies hinder the extraction of tracker genes to analyze the course of biological events. In this study, we demonstrate the applications of supervised machine learning methods to reduce the irrelevance in microarray data series and thereby extract robust molecular markers to track biological processes. The methodology has been illustrated by analyzing whole genome expression studies on bone-implant integration (ossointegration). Being a biological process, osseointegration is known to leave a trail of genetic footprint during the course. In spite of existence of enormous amount of raw data in public repositories, researchers still do not have access to a panel of genes that can definitively track osseointegration. The results from our study revealed panels comprising of matrix metalloproteinases and collagen genes were able to track osseointegration on implant surfaces (MMP9 and COL1A2 on micro-textured; MMP12 and COL6A3 on superimposed nano-textured surfaces) with 100% classification accuracy, specificity and sensitivity. Further, our analysis showed the importance of the progression of the duration in establishment of the mechanical connection at bone-implant surface. The findings from this study are expected to be useful to researchers investigating osseointegration of novel implant materials especially at the early stage. The methodology demonstrated can be easily adapted by scientists in different fields to analyze large databases for other biological processes. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. A Position Controller Model on Color-Based Object Tracking using Fuzzy Logic

    Science.gov (United States)

    Cahyo Wibowo, Budi; Much Ibnu Subroto, Imam; Arifin, Bustanul

    2017-04-01

    Robotics vision is applying technology on the camera to view the environmental conditions as well as the function of the human eye. Colour object tracking system is one application of robotics vision technology with the ability to follow the object being detected. Several methods have been used to generate a good response position control, but most are still using conventional control approach. Fuzzy logic which includes several step of which is to determine the value of crisp input must be fuzzification. The output of fuzzification is forwarded to the process of inference in which there are some fuzzy logic rules. The inference output forwarded to the process of defuzzification to be transformed into outputs (crisp output) to drive the servo motors on the X-axis and Y-axis. Fuzzy logic control is applied to the color-based object tracking system, the system is successful to follow a moving object with average speed of 7.35 cm/s in environments with 117 lux light intensity.

  1. Binocular visual tracking and grasping of a moving object with a 3D trajectory predictor

    Directory of Open Access Journals (Sweden)

    J. Fuentes‐Pacheco

    2009-12-01

    Full Text Available This paper presents a binocular eye‐to‐hand visual servoing system that is able to track and grasp a moving object in real time.Linear predictors are employed to estimate the object trajectory in three dimensions and are capable of predicting futurepositions even if the object is temporarily occluded. For its development we have used a CRS T475 manipulator robot with sixdegrees of freedom and two fixed cameras in a stereo pair configuration. The system has a client‐server architecture and iscomposed of two main parts: the vision system and the control system. The vision system uses color detection to extract theobject from the background and a tracking technique based on search windows and object moments. The control system usesthe RobWork library to generate the movement instructions and to send them to a C550 controller by means of the serial port.Experimental results are presented to verify the validity and the efficacy of the proposed visual servoing system.

  2. Position Affects Performance in Multiple-Object Tracking in Rugby Union Players

    Directory of Open Access Journals (Sweden)

    Andrés Martín

    2017-09-01

    Full Text Available We report an experiment that examines the performance of rugby union players and a control group composed of graduate student with no sport experience, in a multiple-object tracking task. It compares the ability of 86 high level rugby union players grouped as Backs and Forwards and the control group, to track a subset of randomly moving targets amongst the same number of distractors. Several difficulties were included in the experimental design in order to evaluate possible interactions between the relevant variables. Results show that the performance of the Backs is better than that of the other groups, but the occurrence of interactions precludes an isolated groups analysis. We interpret the results within the framework of visual attention and discuss both, the implications of our results and the practical consequences.

  3. Reducing regional vulnerabilities and multi-city robustness conflicts using many-objective optimization under deep uncertainty

    Science.gov (United States)

    Reed, Patrick; Trindade, Bernardo; Jonathan, Herman; Harrison, Zeff; Gregory, Characklis

    2016-04-01

    Emerging water scarcity concerns in southeastern US are associated with several deeply uncertain factors, including rapid population growth, limited coordination across adjacent municipalities and the increasing risks for sustained regional droughts. Managing these uncertainties will require that regional water utilities identify regionally coordinated, scarcity-mitigating strategies that trigger the appropriate actions needed to avoid water shortages and financial instabilities. This research focuses on the Research Triangle area of North Carolina, seeking to engage the water utilities within Raleigh, Durham, Cary and Chapel Hill in cooperative and robust regional water portfolio planning. Prior analysis of this region through the year 2025 has identified significant regional vulnerabilities to volumetric shortfalls and financial losses. Moreover, efforts to maximize the individual robustness of any of the mentioned utilities also have the potential to strongly degrade the robustness of the others. This research advances a multi-stakeholder Many-Objective Robust Decision Making (MORDM) framework to better account for deeply uncertain factors when identifying cooperative management strategies. Results show that the sampling of deeply uncertain factors in the computational search phase of MORDM can aid in the discovery of management actions that substantially improve the robustness of individual utilities as well as the overall region to water scarcity. Cooperative water transfers, financial risk mitigation tools, and coordinated regional demand management must be explored jointly to decrease robustness conflicts between the utilities. The insights from this work have general merit for regions where adjacent municipalities can benefit from cooperative regional water portfolio planning.

  4. Recent Space PV Concentrator Advances: More Robust, Lighter, and Easier to Track

    Science.gov (United States)

    O'Neill, Mark; McDanal, A. J.; Brandhorst, Henry; Schmid, Kevin; LaCorte, Peter; Piszczor, Michael; Myers, Matt

    2015-01-01

    Over the past three years, the authors have collaborated on several significant advances in space photovoltaic concentrator technology, including a far more robust Fresnel lens for sunlight concentration, improved color-mixing features for the lens to minimize chromatic aberration losses for next-generation 4-junction and 6-junction IMM cells, a new approach to suntracking requiring only one axis of rotation even in the presence of large beta angles (e.g., +/- 50 deg), a new waste heat radiator made of graphene, with 80-90% reduction in mass, and a new platform for deployment and support on orbit (SOLAROSA). These patent-pending advances are described in this paper.

  5. Modeling and Robust Trajectory Tracking Control for a Novel Six-Rotor Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Chengshun Yang

    2013-01-01

    Full Text Available Modeling and trajectory tracking control of a novel six-rotor unmanned aerial vehicle (UAV is concerned to solve problems such as smaller payload capacity and lack of both hardware redundancy and anticrosswind capability for quad-rotor. The mathematical modeling for the six-rotor UAV is developed on the basis of the Newton-Euler formalism, and a second-order sliding-mode disturbance observer (SOSMDO is proposed to reconstruct the disturbances of the rotational dynamics. In consideration of the under-actuated and strong coupling properties of the six-rotor UAV, a nested double loops trajectory tracking control strategy is adopted. In the outer loop, a position error PID controller is designed, of which the task is to compare the desired trajectory with real position of the six-rotor UAV and export the desired attitude angles to the inner loop. In the inner loop, a rapid-convergent nonlinear differentiator (RCND is proposed to calculate the derivatives of the virtual control signal, instead of using the analytical differentiation, to avoid “differential expansion” in the procedure of the attitude controller design. Finally, the validity and effectiveness of the proposed technique are demonstrated by the simulation results.

  6. Rotational Subgroup Voting and Pose Clustering for Robust 3D Object Recognition

    DEFF Research Database (Denmark)

    Buch, Anders Glent; Kiforenko, Lilita; Kraft, Dirk

    2017-01-01

    to their ability to handle noisy and incomplete data. However, this correspondence set is usually contaminated by outliers in practical scenarios, which has led to many past contributions based on robust detectors such as the Hough transform or RANSAC. The key insight of our work is that a single correspondence...

  7. A Continuous Object Boundary Detection and Tracking Scheme for Failure-Prone Sensor Networks.

    Science.gov (United States)

    Imran, Sajida; Ko, Young-Bae

    2017-02-13

    In wireless sensor networks, detection and tracking of continuous natured objects is more challenging owing to their unique characteristics such as uneven expansion and contraction. A continuous object is usually spread over a large area, and, therefore, a substantial number of sensor nodes are needed to detect the object. Nodes communicate with each other as well as with the sink to exchange control messages and report their detection status. The sink performs computations on the received data to estimate the object boundary. For accurate boundary estimation, nodes at the phenomenon boundary need to be carefully selected. Failure of one or multiple boundary nodes (BNs) can significantly affect the object detection and boundary estimation accuracy at the sink. We develop an efficient failure-prone object detection approach that not only detects and recovers from BN failures but also reduces the number and size of transmissions without compromising the boundary estimation accuracy. The proposed approach utilizes the spatial and temporal features of sensor nodes to detect object BNs. A Voronoi diagram-based network clustering, and failure detection and recovery scheme is used to increase boundary estimation accuracy. Simulation results show the significance of our approach in terms of energy efficiency, communication overhead, and boundary accuracy.

  8. Image-based tracking system for vibration measurement of a rotating object using a laser scanning vibrometer

    Science.gov (United States)

    Kim, Dongkyu; Khalil, Hossam; Jo, Youngjoon; Park, Kyihwan

    2016-06-01

    An image-based tracking system using laser scanning vibrometer is developed for vibration measurement of a rotating object. The proposed system unlike a conventional one can be used where the position or velocity sensor such as an encoder cannot be attached to an object. An image processing algorithm is introduced to detect a landmark and laser beam based on their colors. Then, through using feedback control system, the laser beam can track a rotating object.

  9. Image-based tracking system for vibration measurement of a rotating object using a laser scanning vibrometer

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dongkyu, E-mail: akein@gist.ac.kr; Khalil, Hossam; Jo, Youngjoon; Park, Kyihwan, E-mail: khpark@gist.ac.kr [School of Mechatronics, Gwangju Institute of Science and Technology, Buk-gu, Gwangju, South Korea, 500-712 (Korea, Republic of)

    2016-06-28

    An image-based tracking system using laser scanning vibrometer is developed for vibration measurement of a rotating object. The proposed system unlike a conventional one can be used where the position or velocity sensor such as an encoder cannot be attached to an object. An image processing algorithm is introduced to detect a landmark and laser beam based on their colors. Then, through using feedback control system, the laser beam can track a rotating object.

  10. Detecting single-target changes in multiple object tracking: The case of peripheral vision.

    Science.gov (United States)

    Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

    2016-05-01

    In the present study, we investigated whether peripheral vision can be used to monitor multiple moving objects and to detect single-target changes. For this purpose, in Experiment 1, a modified multiple object tracking (MOT) setup with a large projection screen and a constant-position centroid phase had to be checked first. Classical findings regarding the use of a virtual centroid to track multiple objects and the dependency of tracking accuracy on target speed could be successfully replicated. Thereafter, the main experimental variations regarding the manipulation of to-be-detected target changes could be introduced in Experiment 2. In addition to a button press used for the detection task, gaze behavior was assessed using an integrated eyetracking system. The analysis of saccadic reaction times in relation to the motor response showed that peripheral vision is naturally used to detect motion and form changes in MOT, because saccades to the target often occurred after target-change offset. Furthermore, for changes of comparable task difficulties, motion changes are detected better by peripheral vision than are form changes. These findings indicate that the capabilities of the visual system (e.g., visual acuity) affect change detection rates and that covert-attention processes may be affected by vision-related aspects such as spatial uncertainty. Moreover, we argue that a centroid-MOT strategy might reduce saccade-related costs and that eyetracking seems to be generally valuable to test the predictions derived from theories of MOT. Finally, we propose implications for testing covert attention in applied settings.

  11. Object tracking with robotic total stations: Current technologies and improvements based on image data

    Science.gov (United States)

    Ehrhart, Matthias; Lienhart, Werner

    2017-09-01

    The importance of automated prism tracking is increasingly triggered by the rising automation of total station measurements in machine control, monitoring and one-person operation. In this article we summarize and explain the different techniques that are used to coarsely search a prism, to precisely aim at a prism, and to identify whether the correct prism is tracked. Along with the state-of-the-art review, we discuss and experimentally evaluate possible improvements based on the image data of an additional wide-angle camera which is available for many total stations today. In cases in which the total station's fine aiming module loses the prism, the tracked object may still be visible to the wide-angle camera because of its larger field of view. The theodolite angles towards the target can then be derived from its image coordinates which facilitates a fast reacquisition of the prism. In experimental measurements we demonstrate that our image-based approach for the coarse target search is 4 to 10-times faster than conventional approaches.

  12. Eye Tracking Research and Technology: Towards Objective Measurement of Data Quality.

    Science.gov (United States)

    Reingold, Eyal M

    2014-03-01

    Two methods for objectively measuring eye tracking data quality are explored. The first method works by tricking the eye tracker to detect an abrupt change in the gaze position of an artificial eye that in actuality does not move. Such a device, referred to as an artificial saccade generator, is shown to be extremely useful for measuring the temporal accuracy and precision of eye tracking systems and for validating the latency to display change in gaze contingent display paradigms. The second method involves an artificial pupil that is mounted on a computer controlled moving platform. This device is designed to be able to provide the eye tracker with motion sequences that closely resemble biological eye movements. The main advantage of using artificial motion for testing eye tracking data quality is the fact that the spatiotemporal signal is fully specified in a manner independent of the eye tracker that is being evaluated and that nearly identical motion sequence can be reproduced multiple times with great precision. The results of the present study demonstrate that the equipment described has the potential to become an important tool in the comprehensive evaluation of data quality.

  13. Robust finite-time tracking control for nonlinear suspension systems via disturbance compensation

    Science.gov (United States)

    Pan, Huihui; Jing, Xingjian; Sun, Weichao

    2017-05-01

    This paper focuses on the finite-time tracking control with external disturbance for active suspension systems. In order to compensate unknown disturbance efficiently, a disturbance compensator with finite-time convergence property is studied. By analyzing the discontinuous phenomenon of classical disturbance compensation techniques, this study presents a simple approach to construct a continuous compensator satisfying the finite-time disturbance rejection performance. According to the finite-time separation principle, the design procedures of the nominal controller for the suspension system without disturbance and the disturbance compensator can be implemented in a completely independent manner. Therefore, the overall control law for the closed-loop system is continuous, which offers some distinct advantages over the existing discontinuous ones. From the perspective of practical implementation, the continuous controller can avoid effectively the unexpected chattering in active suspension control. Comparative experimental results are presented and discussed to illustrate the advantage and effectiveness of the proposed control strategy.

  14. Noise-robust cortical tracking of attended speech in real-world acoustic scenes

    DEFF Research Database (Denmark)

    Fuglsang, Søren; Dau, Torsten; Hjortkjær, Jens

    2017-01-01

    Selectively attending to one speaker in a multi-speaker scenario is thought to synchronize low-frequency cortical activity to the attended speech signal. In recent studies, reconstruction of speech from single-trial electroencephalogram (EEG) data has been used to decode which talker a listener...... is attending to in a two-talker situation. It is currently unclear how this generalizes to more complex sound environments. Behaviorally, speech perception is robust to the acoustic distortions that listeners typically encounter in everyday life, but it is unknown whether this is mirrored by a noise...... of a particular talker. Across the different listening environments, we found that the attended talker could be accurately decoded from single-trial EEG data irrespective of the different distortions in the acoustic input. For highly reverberant environments, speech envelopes reconstructed from neural responses...

  15. Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

    Science.gov (United States)

    Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

    1992-01-01

    A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

  16. Tracking 3D Moving Objects Based on GPS/IMU Navigation Solution, Laser Scanner Point Cloud and GIS Data

    Directory of Open Access Journals (Sweden)

    Siavash Hosseinyalamdary

    2015-07-01

    Full Text Available Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM, can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS and Inertial Measurement Unit (IMU navigation solution.

  17. Reducing regional drought vulnerabilities and multi-city robustness conflicts using many-objective optimization under deep uncertainty

    Science.gov (United States)

    Trindade, B. C.; Reed, P. M.; Herman, J. D.; Zeff, H. B.; Characklis, G. W.

    2017-06-01

    Emerging water scarcity concerns in many urban regions are associated with several deeply uncertain factors, including rapid population growth, limited coordination across adjacent municipalities and the increasing risks for sustained regional droughts. Managing these uncertainties will require that regional water utilities identify coordinated, scarcity-mitigating strategies that trigger the appropriate actions needed to avoid water shortages and financial instabilities. This research focuses on the Research Triangle area of North Carolina, seeking to engage the water utilities within Raleigh, Durham, Cary and Chapel Hill in cooperative and robust regional water portfolio planning. Prior analysis of this region through the year 2025 has identified significant regional vulnerabilities to volumetric shortfalls and financial losses. Moreover, efforts to maximize the individual robustness of any of the mentioned utilities also have the potential to strongly degrade the robustness of the others. This research advances a multi-stakeholder Many-Objective Robust Decision Making (MORDM) framework to better account for deeply uncertain factors when identifying cooperative drought management strategies. Our results show that appropriately designing adaptive risk-of-failure action triggers required stressing them with a comprehensive sample of deeply uncertain factors in the computational search phase of MORDM. Search under the new ensemble of states-of-the-world is shown to fundamentally change perceived performance tradeoffs and substantially improve the robustness of individual utilities as well as the overall region to water scarcity. Search under deep uncertainty enhanced the discovery of how cooperative water transfers, financial risk mitigation tools, and coordinated regional demand management must be employed jointly to improve regional robustness and decrease robustness conflicts between the utilities. Insights from this work have general merit for regions where

  18. Rotation Matrix to Operate a Robot Manipulator for 2D Analog Tracking Objects Using Electrooculography

    Directory of Open Access Journals (Sweden)

    Muhammad Ilhamdi Rusydi

    2014-07-01

    Full Text Available Performing some special tasks using electrooculography (EOG in daily activities is being developed in various areas. In this paper, simple rotation matrixes were introduced to help the operator move a 2-DoF planar robot manipulator. The EOG sensor, NF 5201, has two output channels (Ch1 and Ch2, as well as one ground channel and one reference channel. The robot movement was the indicator that this system could follow gaze motion based on EOG. Operators gazed into five training target points each in the horizontal and vertical line as the preliminary experiments, which were based on directions, distances and the areas of gaze motions. This was done to get the relationships between EOG and gaze motion distance for four directions, which were up, down, right and left. The maximum angle for the horizontal was 46°, while it was 38° for the vertical. Rotation matrixes for the horizontal and vertical signals were combined, so as to diagonally track objects. To verify, the errors between actual and desired target positions were calculated using the Euclidian distance. This test section had 20 random target points. The result indicated that this system could track an object with average angle errors of 3.31° in the x-axis and 3.58° in the y-axis.

  19. Gait Tracking Control of Quadruped Robot Using Differential Evolution Based Structure Specified Mixed Sensitivity H∞ Robust Control

    Directory of Open Access Journals (Sweden)

    Petrus Sutyasadi

    2016-01-01

    Full Text Available This paper proposed a control algorithm that guarantees gait tracking performance for quadruped robots. During dynamic gait motion, such as trotting, the quadruped robot is unstable. In addition to uncertainties of parameters and unmodeled dynamics, the quadruped robot always faces some disturbances. The uncertainties and disturbances contribute significant perturbation to the dynamic gait motion control of the quadruped robot. Failing to track the gait pattern properly propagates instability to the whole system and can cause the robot to fall. To overcome the uncertainties and disturbances, structured specified mixed sensitivity H∞ robust controller was proposed to control the quadruped robot legs’ joint angle positions. Before application to the real hardware, the proposed controller was tested on the quadruped robot’s leg planar dynamic model using MATLAB. The proposed controller can control the robot’s legs efficiently even under uncertainties from a set of model parameter variations. The robot was also able to maintain its stability even when it was tested under several terrain disturbances.

  20. An AEGIS-CPHD Filter to Maintain Custody of GEO Space Objects with Limited Tracking Data

    Science.gov (United States)

    Gehly, S.; Jones, B.; Axelrad, P.

    2014-09-01

    The problem of space situational awareness (SSA) involves characterizing space objects subject to nonlinear dynamics and sparse measurements. Space objects in GEO are primarily tracked using optical sensors, which have limited fields of view, imperfect ability to detect objects, and are limited to taking measurements at night, all of which result in large gaps between measurements. In addition, the nonlinear dynamics result in state uncertainty representations which are generally non-Gaussian. When estimating the states of a catalog of space objects, these issues must be resolved within the framework of a multitarget filter. To address the issue of non-Gaussian uncertainty, the Adaptive Entropy-based Gaussian-mixture Information Synthesis (AEGIS) filter can be used. AEGIS is an implementation of the Unscented Kalman Filter (UKF) using an adaptive number of Gaussian mixture components to approximate the non-Gaussian state probability density function (pdf). Mixture components are split when nonlinearity is detected during propagation, typically during long data gaps, and can be merged or removed following measurement updates to reduce computational effort. Previous research has examined the use of AEGIS in multitarget filters based in Finite Set Statistics (FISST), including the Probability Hypothesis Density (PHD) filter and Cardinalized PHD (CPHD) filter. This paper uses the CPHD filter because in other applications it has been demonstrated to be more effective at estimating and maintaining the cardinality, or number of objects present, when objects are often leaving the sensor field of view (FOV). An important consideration in implementing the filter is the computation of the probability of detection. Existing formulations use a state-dependent probability of detection to assign a value based on whether the mean estimated state is in the sensor FOV. This paper employs a more realistic development by mapping the full state pdf into measurement space and

  1. Robust boundary detection and tracking of left ventricles on ultrasound images using active shape model and ant colony optimization.

    Science.gov (United States)

    Zhang, Yaonan; Gao, Yuan; Jiao, Jinling; Li, Xian; Li, Sai; Yang, Jun

    2014-01-01

    Information regarding the motion, strain and synchronization are important for cardiac diagnosis and therapy. Extraction of such information from ultrasound images remains an open problem till today. In this paper, a novel method is proposed to extract the boundaries of left ventricles and track these boundaries in ultrasound image sequences. The initial detection of boundaries was performed by an active shape model scheme. Subsequent refinement of the boundaries was done by using local variance information of the images. The main objective of this paper is the formulation of a new boundary tracking algorithm using ant colony optimization technique. The experiments conducted on the simulated image sequences and the real cardiac ultrasound image sequences shows a positive and promising result.

  2. A mean–variance objective for robust production optimization in uncertain geological scenarios

    DEFF Research Database (Denmark)

    Capolei, Andrea; Suwartadi, Eka; Foss, Bjarne

    2014-01-01

    borehole pressures are computed by solution of an optimal control problem that maximizes a financial measure such as the Net Present Value (NPV). The NPV is a stochastic variable as the reservoir parameters, such as the permeability field, are stochastic. In certainty equivalence optimization, the mean...... value of the permeability field is used in the maximization of the NPV of the reservoir over its lifetime. This approach neglects the significant uncertainty in the NPV. Robust optimization maximizes the expected NPV over an ensemble of permeability fields to overcome this shortcoming of certainty...

  3. A Low-Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of-Interest Based Rate Controller

    Science.gov (United States)

    2017-03-01

    A Low-Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of- Interest Based Rate Controller Jong Hwan Ko...military surveillance, with a noise-robust moving object detection and region-of- interest based rate controller. The improved robustness to noise...detection, Region-of- interest , Rate control Introduction In wireless image sensor nodes for moving object surveillance, energy efficiency can be

  4. Multi-Objective Memetic Search for Robust Motion and Distortion Correction in Diffusion MRI.

    Science.gov (United States)

    Hering, Jan; Wolf, Ivo; Maier-Hein, Klaus H

    2016-10-01

    Effective image-based artifact correction is an essential step in the analysis of diffusion MR images. Many current approaches are based on retrospective registration, which becomes challenging in the realm of high b -values and low signal-to-noise ratio, rendering the corresponding correction schemes more and more ineffective. We propose a novel registration scheme based on memetic search optimization that allows for simultaneous exploitation of different signal intensity relationships between the images, leading to more robust registration results. We demonstrate the increased robustness and efficacy of our method on simulated as well as in vivo datasets. In contrast to the state-of-art methods, the median target registration error (TRE) stayed below the voxel size even for high b -values (3000 s ·mm -2 and higher) and low SNR conditions. We also demonstrate the increased precision in diffusion-derived quantities by evaluating Neurite Orientation Dispersion and Density Imaging (NODDI) derived measures on a in vivo dataset with severe motion artifacts. These promising results will potentially inspire further studies on metaheuristic optimization in diffusion MRI artifact correction and image registration in general.

  5. Rotational Subgroup Voting and Pose Clustering for Robust 3D Object Recognition

    DEFF Research Database (Denmark)

    Buch, Anders Glent; Kiforenko, Lilita; Kraft, Dirk

    2017-01-01

    estimation. We then apply our method to four state of the art data sets for 3D object recognition that contain occluded and cluttered scenes. Our method achieves perfect recall on two LIDAR data sets and outperforms competing methods on two RGB-D data sets, thus setting a new standard for general 3D object...

  6. Straightforward multi-object video tracking for quantification of mosquito flight activity.

    Science.gov (United States)

    Wilkinson, David A; Lebon, Cyrille; Wood, Trevor; Rosser, Gabriel; Gouagna, Louis Clément

    2014-12-01

    Mosquito flight activity has been studied using a variety of different methodologies, and largely concentrates on female mosquito activity as vectors of disease. Video recording using standard commercially available hardware has limited accuracy for the measurement of flight activity due to the lack of depth-perception in two-dimensional images, but multi-camera observation for three dimensional trajectory reconstructions remain challenging and inaccessible to the majority of researchers. Here, in silico simulations were used to quantify the limitations of two-dimensional flight observation. We observed that, under the simulated conditions, two dimensional observation of flight was more than 90% accurate for the determination of population flight speeds and thus that two dimensional imaging can be used to provide accurate estimates of mosquito population flight speeds, and to measure flight activity over long periods of time. We optimized single camera video imaging to study male Aedes albopictus mosquitoes over a 30 h time period, and tested two different multi-object tracking algorithms for their efficiency in flight tracking. A. Albopictus males were observed to be most active at the start of the day period (06h00-08h00) with the longest period of activity in the evening (15h00-18h00) and that a single mosquito will fly more than 600 m over the course of 24 h. No activity was observed during the night period (18h00-06h00). Simplistic tracking methodologies, executable on standard computational hardware, are sufficient to produce reliable data when video imaging is optimized under laboratory conditions. As this methodology does not require overly-expensive equipment, complex calibration of equipment or extensive knowledge of computer programming, the technology should be accessible to the majority of computer-literate researchers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Critical object recognition in millimeter-wave images with robustness to rotation and scale.

    Science.gov (United States)

    Mohammadzade, Hoda; Ghojogh, Benyamin; Faezi, Sina; Shabany, Mahdi

    2017-06-01

    Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper proposes a novel pre-processing method for canceling rotation and scale using principal component analysis. In addition, a two-layer classification method is introduced and utilized for recognition. Moreover, a large dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as support vector machines can recognize 45.5% of a type of critical objects at 34.2% false alarm rate (FAR), which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR, which indicates a highly significant improvement. The significant contribution of this work is to introduce a new method for analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noted in the field of millimeter-wave image analysis.

  8. Pursuit-evasion games with information uncertainties for elusive orbital maneuver and space object tracking

    Science.gov (United States)

    Shen, Dan; Jia, Bin; Chen, Genshe; Blasch, Erik; Pham, Khanh

    2015-05-01

    This paper develops and evaluates a pursuit-evasion (PE) game approach for elusive orbital maneuver and space object tracking. Unlike the PE games in the literature, where the assumption is that either both players have perfect knowledge of the opponents' positions or use primitive sensing models, the proposed PE approach solves the realistic space situation awareness (SSA) problem with imperfect information, where the evaders will exploit the pursuers' sensing and tracking models to confuse their opponents by maneuvering their orbits to increase the uncertainties, which the pursuers perform orbital maneuvers to minimize. In the game setup, each game player P (pursuer) and E (evader) has its own motion equations with a small continuous low-thrust. The magnitude of the low thrust is fixed and the direction can be controlled by the associated game player. The entropic uncertainty is used to generate the cost functions of game players. The Nash or mixed Nash equilibrium is composed of the directional controls of low-thrusts. Numerical simulations are emulated to demonstrate the performance. Simplified perturbations models (SGP4/SDP4) are exploited to calculate the ground truth of the satellite states (position and speed).

  9. Robot soccer anywhere: achieving persistent autonomous navigation, mapping, and object vision tracking in dynamic environments

    Science.gov (United States)

    Dragone, Mauro; O'Donoghue, Ruadhan; Leonard, John J.; O'Hare, Gregory; Duffy, Brian; Patrikalakis, Andrew; Leederkerken, Jacques

    2005-06-01

    The paper describes an ongoing effort to enable autonomous mobile robots to play soccer in unstructured, everyday environments. Unlike conventional robot soccer competitions that are usually held on purpose-built robot soccer "fields", in our work we seek to develop the capability for robots to demonstrate aspects of soccer-playing in more diverse environments, such as schools, hospitals, or shopping malls, with static obstacles (furniture) and dynamic natural obstacles (people). This problem of "Soccer Anywhere" presents numerous research challenges including: (1) Simultaneous Localization and Mapping (SLAM) in dynamic, unstructured environments, (2) software control architectures for decentralized, distributed control of mobile agents, (3) integration of vision-based object tracking with dynamic control, and (4) social interaction with human participants. In addition to the intrinsic research merit of these topics, we believe that this capability would prove useful for outreach activities, in demonstrating robotics technology to primary and secondary school students, to motivate them to pursue careers in science and engineering.

  10. Detection and objects tracking present in 2D digital video with Matlab

    Directory of Open Access Journals (Sweden)

    Melvin Ramírez Bogantes

    2013-09-01

    Full Text Available This paper presents the main results of research obtained in the design of an algorithm to detect and track an object in a video recording. The algorithm was designed in MatLab software and the videos used, which  presence of the mite Varroa Destructor in the cells of Africanized Honey Bees, were provided by the Centro de Investigación Apícola Tropical (CINAT-UNA.  The main result is the creation of a program capable of detecting and recording the movement of the mite, this is something innovative and useful for studies of the behavior of this species in the cells of honey bees performing the CINAT.

  11. Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology

    Directory of Open Access Journals (Sweden)

    Pandu Sandi Pratama

    2012-12-01

    Full Text Available This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition. [Keywords— Obstacle avoidance, AGV, differential drive, laser measurement system, laser navigation system].

  12. A multi-objective robust optimization model for logistics planning in the earthquake response phase

    NARCIS (Netherlands)

    Najafi, M.; Eshghi, K.; Dullaert, W.E.H.

    2013-01-01

    Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and

  13. What is a Visual Object? Evidence from the Reduced Interference of Grouping in Multiple Object Tracking for Children with Autism Spectrum Disorders

    Directory of Open Access Journals (Sweden)

    Lee de-Wit

    2012-05-01

    Full Text Available Objects offer a critical unit with which we can organise our experience of the world. However, whilst their influence on perception and cognition may be fundamental, understanding how objects are constructed from sensory input remains a key challenge for vision research and psychology in general. A potential window into the means by which objects are constructed in the visual system is offered by the influence that they have on the allocation of attention. In Multiple Object Tracking (MOT, for example, attention is automatically allocated to whole objects, even when this interferes with the tracking of the parts of these objects. In this study we demonstrate that this default tendency to track whole objects is reduced in children with Autisim Spectrum Disorders (ASD. This result both validates the use of MOT as a window into how objects are generated in the visual system and highlights how the reduced bias towards more global processing in ASD could influence further stages of cognition by altering the way in which attention selects information for further processing.

  14. Robust 3D object localization and pose estimation for random bin picking with the 3DMaMa algorithm

    Science.gov (United States)

    Skotheim, Øystein; Thielemann, Jens T.; Berge, Asbjørn; Sommerfelt, Arne

    2010-02-01

    Enabling robots to automatically locate and pick up randomly placed and oriented objects from a bin is an important challenge in factory automation, replacing tedious and heavy manual labor. A system should be able to recognize and locate objects with a predefined shape and estimate the position with the precision necessary for a gripping robot to pick it up. We describe a system that consists of a structured light instrument for capturing 3D data and a robust approach for object location and pose estimation. The method does not depend on segmentation of range images, but instead searches through pairs of 2D manifolds to localize candidates for object match. This leads to an algorithm that is not very sensitive to scene complexity or the number of objects in the scene. Furthermore, the strategy for candidate search is easily reconfigurable to arbitrary objects. Experiments reported in this paper show the utility of the method on a general random bin picking problem, in this paper exemplified by localization of car parts with random position and orientation. Full pose estimation is done in less than 380 ms per image. We believe that the method is applicable for a wide range of industrial automation problems where precise localization of 3D objects in a scene is needed.

  15. Effect of age and stereopsis on a multiple-object tracking task.

    Directory of Open Access Journals (Sweden)

    Marjolaine Plourde

    Full Text Available 3D vision develops during childhood and tends to diminish after 65 years of age. It is still relatively unknown how stereopsis is used in more complex/ecological contexts such as when walking about in crowds where objects are in motion and occlusions occur. One task that shares characteristics with the requirements for processing dynamic crowds is the multiple object-tracking task (MOT. In the present study we evaluated the impact of stereopsis on a MOT task as a function of age. A total of 60 observers consisting of three groups of 20 subjects (7-12 years old, 18-40 years old and 65 years and older completed the task in both conditions (with and without stereoscopic effects. The adult group obtained the better scores, followed by the children and the older adult group. The performance difference between the stereoscopic and non-stereoscopic conditions was significant and similar for the adults and the children but was non significant for the older observers. These results show that stereopsis helps children and adults accomplish a MOT task, but has no impact on older adults' performances. The present results have implications as to how populations differ in their efficiency of using stereoscopic cues for disambiguating complex dynamic scenes.

  16. Effect of age and stereopsis on a multiple-object tracking task

    Science.gov (United States)

    2017-01-01

    3D vision develops during childhood and tends to diminish after 65 years of age. It is still relatively unknown how stereopsis is used in more complex/ecological contexts such as when walking about in crowds where objects are in motion and occlusions occur. One task that shares characteristics with the requirements for processing dynamic crowds is the multiple object-tracking task (MOT). In the present study we evaluated the impact of stereopsis on a MOT task as a function of age. A total of 60 observers consisting of three groups of 20 subjects (7–12 years old, 18–40 years old and 65 years and older) completed the task in both conditions (with and without stereoscopic effects). The adult group obtained the better scores, followed by the children and the older adult group. The performance difference between the stereoscopic and non-stereoscopic conditions was significant and similar for the adults and the children but was non significant for the older observers. These results show that stereopsis helps children and adults accomplish a MOT task, but has no impact on older adults’ performances. The present results have implications as to how populations differ in their efficiency of using stereoscopic cues for disambiguating complex dynamic scenes. PMID:29244875

  17. Pupil Sizes Scale with Attentional Load and Task Experience in a Multiple Object Tracking Task.

    Directory of Open Access Journals (Sweden)

    Basil Wahn

    Full Text Available Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted on three consecutive days. We found that pupil sizes increased with each increment in attentional load. Across days, we found systematic pupil size reductions. We compared the model fit for predicting pupil size modulations using attentional load, task experience, and task performance as predictors. We found that a model which included attentional load and task experience as predictors had the best model fit while adding performance as a predictor to this model reduced the overall model fit. Overall, results suggest that pupillometry provides a viable metric for precisely assessing attentional load and task experience in visuospatial tasks.

  18. Pupil Sizes Scale with Attentional Load and Task Experience in a Multiple Object Tracking Task.

    Science.gov (United States)

    Wahn, Basil; Ferris, Daniel P; Hairston, W David; König, Peter

    2016-01-01

    Previous studies have related changes in attentional load to pupil size modulations. However, studies relating changes in attentional load and task experience on a finer scale to pupil size modulations are scarce. Here, we investigated how these changes affect pupil sizes. To manipulate attentional load, participants covertly tracked between zero and five objects among several randomly moving objects on a computer screen. To investigate effects of task experience, the experiment was conducted on three consecutive days. We found that pupil sizes increased with each increment in attentional load. Across days, we found systematic pupil size reductions. We compared the model fit for predicting pupil size modulations using attentional load, task experience, and task performance as predictors. We found that a model which included attentional load and task experience as predictors had the best model fit while adding performance as a predictor to this model reduced the overall model fit. Overall, results suggest that pupillometry provides a viable metric for precisely assessing attentional load and task experience in visuospatial tasks.

  19. Risk- and robustness-based solutions to a multi-objective water distribution system rehabilitation problem under uncertainty .

    Science.gov (United States)

    Kapelan, Z; Savic, D A; Walters, G A; Babayan, A V

    2006-01-01

    The water distribution system (WDS) rehabilitation problem is defined here as a multi-objective optimisation problem under uncertainty. Two alternative problem formulations are considered. The first objective in both approaches is to minimise the total rehabilitation cost. The second objective is to either maximise the overall WDS robustness or to minimise the total WDS risk. The WDS robustness is defined as the probability of simultaneously satisfying minimum pressure head constraints at all nodes in the network. Total risk is defined as the sum of nodal risks, where nodal risk is defined as the product of the probability of pressure failure at that node and consequence of such failure. Decision variables are the alternative rehabilitation options for each pipe in the network. The only source of uncertainty is the future water consumption. Uncertain demands are modelled using any probability density functions (PDFs) assigned in the problem formulation phase. The corresponding PDFs of the analysed nodal heads are calculated using the Latin Hypercube sampling technique. The optimal rehabilitation problem is solved using the newly developed rNSGAII method which is a modification of the well-known NSGAII optimisation algorithm. In rNSGAII a small number of demand samples are used for each fitness evaluation leading to significant computational savings when compared to the full sampling approach. The two alternative approaches are tested, verified and their performance compared on the New York tunnels case study. The results obtained demonstrate that both new methodologies are capable of identifying the robust (near) Pareto optimal fronts while making significant computational savings.

  20. Using multi-objective robust decision making to support seasonal water management in the Chao Phraya River basin, Thailand

    Science.gov (United States)

    Riegels, Niels; Jessen, Oluf; Madsen, Henrik

    2016-04-01

    A multi-objective robust decision making approach is demonstrated that supports seasonal water management in the Chao Phraya River basin in Thailand. The approach uses multi-objective optimization to identify a Pareto-optimal set of management alternatives. Ensemble simulation is used to evaluate how each member of the Pareto set performs under a range of uncertain future conditions, and a robustness criterion is used to select a preferred alternative. Data mining tools are then used to identify ranges of uncertain factor values that lead to unacceptable performance for the preferred alternative. The approach is compared to a multi-criteria scenario analysis approach to estimate whether the introduction of additional complexity has the potential to improve decision making. Dry season irrigation in Thailand is managed through non-binding recommendations about the maximum extent of rice cultivation along with incentives for less water-intensive crops. Management authorities lack authority to prevent river withdrawals for irrigation when rice cultivation exceeds recommendations. In practice, this means that water must be provided to irrigate the actual planted area because of downstream municipal water supply requirements and water quality constraints. This results in dry season reservoir withdrawals that exceed planned withdrawals, reducing carryover storage to hedge against insufficient wet season runoff. The dry season planning problem in Thailand can therefore be framed in terms of decisions, objectives, constraints, and uncertainties. Decisions include recommendations about the maximum extent of rice cultivation and incentives for growing less water-intensive crops. Objectives are to maximize benefits to farmers, minimize the risk of inadequate carryover storage, and minimize incentives. Constraints include downstream municipal demands and water quality requirements. Uncertainties include the actual extent of rice cultivation, dry season precipitation, and

  1. Tracking initially unresolved thrusting objects in 3D using a single stationary optical sensor

    Science.gov (United States)

    Lu, Qin; Bar-Shalom, Yaakov; Willett, Peter; Granström, Karl; Ben-Dov, R.; Milgrom, B.

    2017-05-01

    This paper considers the problem of estimating the 3D states of a salvo of thrusting/ballistic endo-atmospheric objects using 2D Cartesian measurements from the focal plane array (FPA) of a single fixed optical sensor. Since the initial separations in the FPA are smaller than the resolution of the sensor, this results in merged measurements in the FPA, compounding the usual false-alarm and missed-detection uncertainty. We present a two-step methodology. First, we assume a Wiener process acceleration (WPA) model for the motion of the images of the projectiles in the optical sensor's FPA. We model the merged measurements with increased variance, and thence employ a multi-Bernoulli (MB) filter using the 2D measurements in the FPA. Second, using the set of associated measurements for each confirmed MB track, we formulate a parameter estimation problem, whose maximum likelihood estimate can be obtained via numerical search and can be used for impact point prediction. Simulation results illustrate the performance of the proposed method.

  2. Tracking Systems for Virtual Rehabilitation: Objective Performance vs. Subjective Experience. A Practical Scenario

    Directory of Open Access Journals (Sweden)

    Roberto Lloréns

    2015-03-01

    Full Text Available Motion tracking systems are commonly used in virtual reality-based interventions to detect movements in the real world and transfer them to the virtual environment. There are different tracking solutions based on different physical principles, which mainly define their performance parameters. However, special requirements have to be considered for rehabilitation purposes. This paper studies and compares the accuracy and jitter of three tracking solutions (optical, electromagnetic, and skeleton tracking in a practical scenario and analyzes the subjective perceptions of 19 healthy subjects, 22 stroke survivors, and 14 physical therapists. The optical tracking system provided the best accuracy (1.074 ± 0.417 cm while the electromagnetic device provided the most inaccurate results (11.027 ± 2.364 cm. However, this tracking solution provided the best jitter values (0.324 ± 0.093 cm, in contrast to the skeleton tracking, which had the worst results (1.522 ± 0.858 cm. Healthy individuals and professionals preferred the skeleton tracking solution rather than the optical and electromagnetic solution (in that order. Individuals with stroke chose the optical solution over the other options. Our results show that subjective perceptions and preferences are far from being constant among different populations, thus suggesting that these considerations, together with the performance parameters, should be also taken into account when designing a rehabilitation system.

  3. Functional connectivity indicates differential roles for the intraparietal sulcus and the superior parietal lobule in multiple object tracking.

    Science.gov (United States)

    Alnæs, Dag; Sneve, Markus H; Richard, Geneviève; Skåtun, Kristina C; Kaufmann, Tobias; Nordvik, Jan Egil; Andreassen, Ole A; Endestad, Tor; Laeng, Bruno; Westlye, Lars T

    2015-12-01

    Attentive tracking requires sustained object-based attention, rather than passive vigilance or rapid attentional shifts to brief events. Several theories of tracking suggest a mechanism of indexing objects that allows for attentional resources to be directed toward the moving targets. Imaging studies have shown that cortical areas belonging to the dorsal frontoparietal attention network increase BOLD-signal during multiple object tracking (MOT). Among these areas, some studies have assigned IPS a particular role in object indexing, but the neuroimaging evidence has been sparse. In the present study, we tested participants on a continuous version of the MOT task in order to investigate how cortical areas engage in functional networks during attentional tracking. Specifically, we analyzed the data using eigenvector centrality mapping (ECM) analysis, which provides estimates of individual voxels' connectedness with hub-like parts of the functional network. The results obtained using permutation based voxel-wise statistics support the proposed role for the IPS in object indexing as this region displayed increased centrality during tracking as well as increased functional connectivity with both prefrontal and visual perceptual cortices. In contrast, the opposite pattern was observed for the SPL, with decreasing centrality, as well as reduced functional connectivity with the visual and frontal cortices, in agreement with a hypothesized role for SPL in attentional shifts. These findings provide novel evidence that IPS and SPL serve different functional roles during MOT, while at the same time being highly engaged during tracking as measured by BOLD-signal changes. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Robust Multi-Objective Global Optimization of Stochastic Processes With a Case Study in Gradient Elution Chromatography.

    Science.gov (United States)

    Freier, Lars; von Lieres, Eric

    2017-09-09

    A novel algorithm for robust multi-objective process optimization under stochastic variability of environmental variables is introduced and applied to a case study in gradient elution chromatography. Process variability is accounted for by simultaneously optimizing several scenarios with random but fixed values of the environmental variables. These iterative optimizations are synchronized by planning the same experiments for all scenarios. Experiments are designed by maximizing the cumulative expected hypervolume improvement as predicted by several Gaussian process regression models. A straightforward method is presented for estimating the expected Pareto front and its variability based on the resulting data that maintains traceability of the corresponding process parameters. This information is required for robust process optimization, that is, determination of Pareto optimal processes that fulfil specific minimal criteria with a certain confidence. The presented algorithm can generally be applied to both in silico and wet lab experiments but involves an increased experimental effort as compared to the deterministic case. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Basic Surgical Skill Retention: Can Patriot Motion Tracking System Provide an Objective Measurement for it?

    Science.gov (United States)

    Shaharan, Shazrinizam; Nugent, Emmeline; Ryan, Donncha M; Traynor, Oscar; Neary, Paul; Buckley, Declan

    2016-01-01

    Knot tying is a fundamental skill that surgical trainees have to learn early on in their training. The aim of this study was to establish the predictive and concurrent validity of the Patriot as an assessment tool and determine the skill retention in first-year surgical trainees after 5 months of training. First-year surgical trainees were recruited in their first month of the training program. Experts were invited to set the proficiency level. The subjects performed hand knot tying on a bench model. The skill was assessed at baseline in the first month of training and at 5 months. The assessment tools were the Patriot electromagnetic tracking system and Objective Structured Assessment of Technical Skills (OSATS). The trainees' scores were compared to the proficiency score. The data were analyzed using paired t-test and Pearson correlation analysis. A total of 14 first-year trainees participated in this study. The time taken to complete the task and the path length (PL) were significantly shorter (p = 0.007 and p = 0.0085, respectively) at 5 months. OSATS scoring showed a significant improvement (p = 0.0004). There was a significant correlation between PL and OSATS at baseline (r = -0.873) and at Month 5 (r = -0.774). In all, 50% of trainees reached the proficiency PL at baseline and at Month 5. Among them, 3 trainees improved their PL to reach proficiency and the other 3 trainees failed to reach proficiency. The parameters from the Patriot motion tracker demonstrated a significant correlation with the classical observational assessment tool and were capable of highlighting the skill retention in surgical trainees. Therefore, the automated scoring system has a significant role in the surgical training curriculum as an adjunct to the available assessment tool. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  6. Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

    Science.gov (United States)

    Bagherpoor, H M; Salmasi, Farzad R

    2015-07-01

    In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Toward a Robust Security Paradigm for Bluetooth Low Energy-Based Smart Objects in the Internet-of-Things

    Directory of Open Access Journals (Sweden)

    Shi-Cho Cha

    2017-10-01

    Full Text Available Bluetooth Low Energy (BLE has emerged as one of the most promising technologies to enable the Internet-of-Things (IoT paradigm. In BLE-based IoT applications, e.g., wearables-oriented service applications, the Bluetooth MAC addresses of devices will be swapped for device pairings. The random address technique is adopted to prevent malicious users from tracking the victim’s devices with stationary Bluetooth MAC addresses and accordingly the device privacy can be preserved. However, there exists a tradeoff between privacy and security in the random address technique. That is, when device pairing is launched and one device cannot actually identify another one with addresses, it provides an opportunity for malicious users to break the system security via impersonation attacks. Hence, using random addresses may lead to higher security risks. In this study, we point out the potential risk of using random address technique and then present critical security requirements for BLE-based IoT applications. To fulfill the claimed requirements, we present a privacy-aware mechanism, which is based on elliptic curve cryptography, for secure communication and access-control among BLE-based IoT objects. Moreover, to ensure the security of smartphone application associated with BLE-based IoT objects, we construct a Smart Contract-based Investigation Report Management framework (SCIRM which enables smartphone application users to obtain security inspection reports of BLE-based applications of interest with smart contracts.

  8. Toward a Robust Security Paradigm for Bluetooth Low Energy-Based Smart Objects in the Internet-of-Things.

    Science.gov (United States)

    Cha, Shi-Cho; Yeh, Kuo-Hui; Chen, Jyun-Fu

    2017-10-14

    Bluetooth Low Energy (BLE) has emerged as one of the most promising technologies to enable the Internet-of-Things (IoT) paradigm. In BLE-based IoT applications, e.g., wearables-oriented service applications, the Bluetooth MAC addresses of devices will be swapped for device pairings. The random address technique is adopted to prevent malicious users from tracking the victim's devices with stationary Bluetooth MAC addresses and accordingly the device privacy can be preserved. However, there exists a tradeoff between privacy and security in the random address technique. That is, when device pairing is launched and one device cannot actually identify another one with addresses, it provides an opportunity for malicious users to break the system security via impersonation attacks. Hence, using random addresses may lead to higher security risks. In this study, we point out the potential risk of using random address technique and then present critical security requirements for BLE-based IoT applications. To fulfill the claimed requirements, we present a privacy-aware mechanism, which is based on elliptic curve cryptography, for secure communication and access-control among BLE-based IoT objects. Moreover, to ensure the security of smartphone application associated with BLE-based IoT objects, we construct a Smart Contract-based Investigation Report Management framework (SCIRM) which enables smartphone application users to obtain security inspection reports of BLE-based applications of interest with smart contracts.

  9. Robust time-domain full waveform inversion with normalized zero-lag cross-correlation objective function

    Science.gov (United States)

    Liu, Youshan; Teng, Jiwen; Xu, Tao; Wang, Yanghua; Liu, Qinya; Badal, José

    2017-04-01

    In full waveform inversion (FWI) with the least-squares (L2) norm, the direct amplitude matching is never perfect and the accurate estimation of the seismic source strength is not always available. In contrast, the normalized zero-lag cross-correlation objective function relaxes on the amplitude constraints and emphasizes the phase information when measuring the closeness between the simulated and observed data. This FWI method becomes insensitive to differences in amplitude. Based on this property, we investigate the effectiveness and robustness of FWI with the normalized zero-lag cross-correlation function (CFWI) against the noise and unpredictable amplitude of the data that cannot be modelled by the wavefield extrapolation operator. The effectiveness is firstly tested by noise-free data and data contaminated by Gaussian white noise. In addition, CFWI can invert the data set with incorrect source strength when compared with the L2 norm. Moreover, the data set with incorrect source signature illustrates that CFWI is slightly more insensitive to the error in source signature than the L2 norm. However, a source inversion is still needed when the source signature is severely erroneous. With non-Gaussian noise data, such as contaminated by strong ground motion noise and even by spike-type noise, CFWI provides a comparable result with that of the robust Huber norm. Numerical experiments with non-Gaussian noise also indicate that CFWI can suppress noise in data to produce clearer images when compared with the Huber norm. Besides, CFWI is free of the threshold criterion that controls the transition between the L2 and L1 norms used with the Huber and Hybrid norms and therefore free from tedious trial-and-error tests. Several numerical examples support that CFWI is an alternative and reliable inversion method. However, a numerical test with a 1-D initial model confirms that CFWI is more sensitive to the cycle-skipping problem caused by less-accurate initial velocity model

  10. Shared processing in multiple object tracking and visual working memory in the absence of response order and task order confounds.

    Science.gov (United States)

    Lapierre, Mark D; Cropper, Simon J; Howe, Piers D L

    2017-01-01

    To understand how the visual system represents multiple moving objects and how those representations contribute to tracking, it is essential that we understand how the processes of attention and working memory interact. In the work described here we present an investigation of that interaction via a series of tracking and working memory dual-task experiments. Previously, it has been argued that tracking is resistant to disruption by a concurrent working memory task and that any apparent disruption is in fact due to observers making a response to the working memory task, rather than due to competition for shared resources. Contrary to this, in our experiments we find that when task order and response order confounds are avoided, all participants show a similar decrease in both tracking and working memory performance. However, if task and response order confounds are not adequately controlled for we find substantial individual differences, which could explain the previous conflicting reports on this topic. Our results provide clear evidence that tracking and working memory tasks share processing resources.

  11. Nested Multi- and Many-Objective Optimisation of Team Track Pursuit Cycling

    Directory of Open Access Journals (Sweden)

    Markus Wagner

    2016-10-01

    Full Text Available Team pursuit track cycling is an elite sport that is part of the Summer Olympics. Teams race against each other on special tracks called velodromes. In this article, we create racing strategies that allow the team to complete the race in as little time as possible. In addition to the traditional minimisation of the race times, we consider the amount of energy that the riders have left at the end of the race. For the team coach this extension can have the benefit that a diverse set of trade-off strategies can be considered. For the optimisation approach, the added diversity can help to get over local optima.To solve this problem, we apply different state-of-the-art algorithms with problem-specific variation operators. It turns out that nesting algorithms is beneficial for achieving fast strategies reliably.

  12. Multi-objective Optimization for the Robust Performance of Drinking Water Treatment Plants under Climate Change and Climate Extremes

    Science.gov (United States)

    Raseman, W. J.; Kasprzyk, J. R.; Rosario-Ortiz, F.; Summers, R. S.; Stewart, J.; Livneh, B.

    2016-12-01

    To promote public health, the United States Environmental Protection Agency (US EPA), and similar entities around the world enact strict laws to regulate drinking water quality. These laws, such as the Stage 1 and 2 Disinfectants and Disinfection Byproducts (D/DBP) Rules, come at a cost to water treatment plants (WTPs) which must alter their operations and designs to meet more stringent standards and the regulation of new contaminants of concern. Moreover, external factors such as changing influent water quality due to climate extremes and climate change, may force WTPs to adapt their treatment methods. To grapple with these issues, decision support systems (DSSs) have been developed to aid WTP operation and planning. However, there is a critical need to better address long-term decision making for WTPs. In this poster, we propose a DSS framework for WTPs for long-term planning, which improves upon the current treatment of deep uncertainties within the overall potable water system including the impact of climate on influent water quality and uncertainties in treatment process efficiencies. We present preliminary results exploring how a multi-objective evolutionary algorithm (MOEA) search can be coupled with models of WTP processes to identify high-performing plans for their design and operation. This coupled simulation-optimization technique uses Borg MOEA, an auto-adaptive algorithm, and the Water Treatment Plant Model, a simulation model developed by the US EPA to assist in creating the D/DBP Rules. Additionally, Monte Carlo sampling methods were used to study the impact of uncertainty of influent water quality on WTP decision-making and generate plans for robust WTP performance.

  13. Impact of mechanism vibration characteristics by joint clearance and optimization design of its multi-objective robustness

    Science.gov (United States)

    Zeng, Baoping; Wang, Chao; Zhang, Yu; Gong, Yajun; Hu, Sanbao

    2017-12-01

    Joint clearances and friction characteristics significantly influence the mechanism vibration characteristics; for example: as for joint clearances, the shaft and bearing of its clearance joint collide to bring about the dynamic normal contact force and tangential coulomb friction force while the mechanism works; thus, the whole system may vibrate; moreover, the mechanism is under contact-impact with impact force constraint from free movement under action of the above dynamic forces; in addition, the mechanism topology structure also changes. The constraint relationship between joints may be established by a repeated complex nonlinear dynamic process (idle stroke - contact-impact - elastic compression - rebound – impact relief - idle stroke movement - contact-impact). Analysis of vibration characteristics of joint parts is still a challenging open task by far. The dynamic equations for any mechanism with clearance is often a set of strong coupling, high-dimensional and complex time-varying nonlinear differential equations which are solved very difficultly. Moreover, complicated chaotic motions very sensitive to initial values in impact and vibration due to clearance let high-precision simulation and prediction of their dynamic behaviors be more difficult; on the other hand, their subsequent wearing necessarily leads to some certain fluctuation of structure clearance parameters, which acts as one primary factor for vibration of the mechanical system. A dynamic model was established to the device for opening the deepwater robot cabin door with joint clearance by utilizing the finite element method and analysis was carried out to its vibration characteristics in this study. Moreover, its response model was carried out by utilizing the DOE method and then the robust optimization design was performed to sizes of the joint clearance and the friction coefficient change range so that the optimization design results may be regarded as reference data for selecting bearings

  14. Optical derotator alignment using image-processing algorithm for tracking laser vibrometer measurements of rotating objects

    Science.gov (United States)

    Khalil, Hossam; Kim, Dongkyu; Jo, Youngjoon; Park, Kyihwan

    2017-06-01

    An optical component called a Dove prism is used to rotate the laser beam of a laser-scanning vibrometer (LSV). This is called a derotator and is used for measuring the vibration of rotating objects. The main advantage of a derotator is that it works independently from an LSV. However, this device requires very specific alignment, in which the axis of the Dove prism must coincide with the rotational axis of the object. If the derotator is misaligned with the rotating object, the results of the vibration measurement are imprecise, owing to the alteration of the laser beam on the surface of the rotating object. In this study, a method is proposed for aligning a derotator with a rotating object through an image-processing algorithm that obtains the trajectory of a landmark attached to the object. After the trajectory of the landmark is mathematically modeled, the amount of derotator misalignment with respect to the object is calculated. The accuracy of the proposed method for aligning the derotator with the rotating object is experimentally tested.

  15. Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers

    Science.gov (United States)

    Chen, Chi-hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

    2017-01-01

    Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories…

  16. Objective Tracking of Tropical Cyclones in the North-West Pacific Basin Based on Wind Field Information only

    Science.gov (United States)

    Leckebusch, G. C.; Befort, D. J.; Kruschke, T.

    2016-12-01

    Although only ca. 12% of the global insured losses of natural disasters occurred in Asia, there are two major reasons to be concerned about risks in Asia: a) The fraction of loss events was substantial higher with 39% of which 94% were due to atmospheric processes; b) Asia and especially China, is undergoing quick transitions and especially the insurance market is rapidly growing. In order to allow for the estimation of potential future (loss) impacts in East-Asia, in this study we further developed and applied a feature tracking system based on extreme wind speed occurrences to tropical cyclones, which was originally developed for extra-tropical cyclones (Leckebusch et al., 2008). In principle, wind fields will be identified and tracked once a coherent exceedance of local percentile thresholds is identified. The focus on severe wind impact will allow an objective link between the strength of a cyclone and its potential damages over land. The wind tracking is developed in such a way to be applicable also to course-gridded AOGCM simulation. In the presented configuration the wind tracking algorithm is applied to the Japanese reanalysis (JRA55) and TC Identification is based on 850hPa wind speeds (6h resolution) from 1979 to 2014 over the Western North Pacific region. For validation the IBTrACS Best Track archive version v03r8 is used. Out of all 904 observed tracks, about 62% can be matched to at least one windstorm event identified in JRA55. It is found that the relative amount of matched best tracks increases with the maximum intensity. Thus, a positive matching (hit rate) of above 98% for Violent Typhoons (VTY), above 90% for Very Strong Typhoons (VSTY), about 75% for Typhoons (TY), and still some 50% for less intense TCs (TD, TS, STS) is found. This result is extremely encouraging to apply this technique to AOGCM outputs and to derive information about affected regions and intensity-frequency distributions potentially changed under future climate conditions.

  17. Persistent Aerial Tracking

    KAUST Repository

    Mueller, Matthias

    2016-04-13

    In this thesis, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photo-realistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the rst evaluation of many state of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. We also present a simulator that can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV "in the field", as well as, generate synthetic but photo-realistic tracking datasets with free ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator will be made publicly available to the vision community to further research in the area of object tracking from UAVs. Additionally, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by \\'handing over the camera\\' from one UAV to another. We integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

  18. Space Object Detection and Tracking Within a Finite Set Statistics Framework

    Science.gov (United States)

    2017-04-13

    MM-YYYY)      21-04-2017 2. REPORT TYPE Final 3. DATES COVERED (From - To) 01 Feb 2015 to 31 Jan 2017 4. TITLE AND SUBTITLE Space Object Detection...description of the data sets used is provided. 3.1 CAMRa Radar Data sets Two types of data sets were obtained from CAMRa: raw and post-processed. For...astronomical images. It detects objects such as stars, satellites, galaxies from FITS images. Then it computes photometry1 from the detected objects and

  19. Post-Newtonian equations of motion for LEO debris objects and space-based acquisition, pointing and tracking laser systems

    Science.gov (United States)

    Gambi, J. M.; García del Pino, M. L.; Gschwindl, J.; Weinmüller, E. B.

    2017-12-01

    This paper deals with the problem of throwing middle-sized low Earth orbit debris objects into the atmosphere via laser ablation. The post-Newtonian equations here provided allow (hypothetical) space-based acquisition, pointing and tracking systems endowed with very narrow laser beams to reach the pointing accuracy presently prescribed. In fact, whatever the orbital elements of these objects may be, these equations will allow the operators to account for the corrections needed to balance the deviations of the line of sight directions due to the curvature of the paths the laser beams are to travel along. To minimize the respective corrections, the systems will have to perform initial positioning manoeuvres, and the shooting point-ahead angles will have to be adapted in real time. The enclosed numerical experiments suggest that neglecting these measures will cause fatal errors, due to differences in the actual locations of the objects comparable to their size.

  20. Robust Real-Time Gradient-based Eye Detection and Tracking Using Transform Domain and PSO-Based Feature Selection

    OpenAIRE

    Salehi, Nasrin.

    2017-01-01

    Despite numerous research on eye detection and tracking, this field of study remains challenging due to the individuality of eyes, occlusion, and variability in scale, location, and light conditions. This paper combines a techniques of feature extraction and a feature selection method to achieve a significant increase in eye recognition. Subspace methods may improve detection efficiency and accuracy of eye centers detection using dimensionality reduction. In this study, HoG descriptor is used...

  1. Spatial and visuospatial working memory tests predict performance in classic multiple-object tracking in young adults, but nonspatial measures of the executive do not.

    Science.gov (United States)

    Trick, Lana M; Mutreja, Rachna; Hunt, Kelly

    2012-02-01

    An individual-differences approach was used to investigate the roles of visuospatial working memory and the executive in multiple-object tracking. The Corsi Blocks and Visual Patterns Tests were used to assess visuospatial working memory. Two relatively nonspatial measures of the executive were used: operation span (OSPAN) and reading span (RSPAN). For purposes of comparison, the digit span test was also included (a measure not expected to correlate with tracking). The tests predicted substantial amounts of variance (R (2) = .33), and the visuospatial measures accounted for the majority (R (2) = .30), with each making a significant contribution. Although the executive measures correlated with each other, the RSPAN did not correlate with tracking. The correlation between OSPAN and tracking was similar in magnitude to that between digit span and tracking (p executive, as measured by tests such as the OSPAN, plays little role in explaining individual differences in multiple-object tracking.

  2. Object-adapted optical trapping and shape-tracking of energy-switching helical bacteria

    Science.gov (United States)

    Koch, Matthias; Rohrbach, Alexander

    2012-10-01

    Optical tweezers are a flexible manipulation tool used to grab micro-objects at a specific point, but a controlled manipulation of objects with more complex or changing shapes is hardly possible. Here, we demonstrate, by time-sharing optical forces, that it is possible to adapt the shape of the trapping potential to the shape of an elongated helical bacterium. In contrast to most other trapped objects, this structure can continuously change its helical shape (and therefore its mechanical energy), making trapping it much more difficult than trapping tiny non-living objects. The shape deformations of the only 200-nm-thin bacterium (Spiroplasma) are measured space-resolved at 800 Hz by exploiting local phase differences in coherently scattered trapping light. By localizing each slope of the bacterium we generate high-contrast, super-resolution movies in three dimensions, without any object staining. This approach will help in investigating the nanomechanics of single wall-less bacteria while reacting to external stimuli on a broad temporal bandwidth.

  3. Handling Occlusions for Robust Augmented Reality Systems

    Directory of Open Access Journals (Sweden)

    Madjid Maidi

    2010-01-01

    Full Text Available In Augmented Reality applications, the human perception is enhanced with computer-generated graphics. These graphics must be exactly registered to real objects in the scene and this requires an effective Augmented Reality system to track the user's viewpoint. In this paper, a robust tracking algorithm based on coded fiducials is presented. Square targets are identified and pose parameters are computed using a hybrid approach based on a direct method combined with the Kalman filter. An important factor for providing a robust Augmented Reality system is the correct handling of targets occlusions by real scene elements. To overcome tracking failure due to occlusions, we extend our method using an optical flow approach to track visible points and maintain virtual graphics overlaying when targets are not identified. Our proposed real-time algorithm is tested with different camera viewpoints under various image conditions and shows to be accurate and robust.

  4. Handling Occlusions for Robust Augmented Reality Systems

    Directory of Open Access Journals (Sweden)

    Maidi Madjid

    2010-01-01

    Full Text Available Abstract In Augmented Reality applications, the human perception is enhanced with computer-generated graphics. These graphics must be exactly registered to real objects in the scene and this requires an effective Augmented Reality system to track the user's viewpoint. In this paper, a robust tracking algorithm based on coded fiducials is presented. Square targets are identified and pose parameters are computed using a hybrid approach based on a direct method combined with the Kalman filter. An important factor for providing a robust Augmented Reality system is the correct handling of targets occlusions by real scene elements. To overcome tracking failure due to occlusions, we extend our method using an optical flow approach to track visible points and maintain virtual graphics overlaying when targets are not identified. Our proposed real-time algorithm is tested with different camera viewpoints under various image conditions and shows to be accurate and robust.

  5. Tracking Neptune’s Migration History through High-perihelion Resonant Trans-Neptunian Objects

    Science.gov (United States)

    Kaib, Nathan A.; Sheppard, Scott S.

    2016-11-01

    Recently, Sheppard et al. presented the discovery of seven new trans-Neptunian objects with moderate eccentricities, perihelia beyond 40 au, and semimajor axes beyond 50 au. Like the few previously known objects on similar orbits, these objects’ semimajor axes are just beyond the Kuiper Belt edge and clustered around Neptunian mean motion resonances (MMRs). These objects likely obtained their observed orbits while trapped within MMRs, when the Kozai-Lidov mechanism raised their perihelia and weakened Neptune’s dynamical influence. Using numerical simulations that model the production of this population, we find that high-perihelion objects near Neptunian MMRs can constrain the nature and timescale of Neptune’s past orbital migration. In particular, the population near the 3:1 MMR (near 62 au) is especially useful due to its large population and short dynamical evolution timescale. If Neptune finishes migrating within ˜100 Myr or less, we predict that over 90% of high-perihelion objects near the 3:1 MMR will have semimajor axes within 1 au of each other, very near the modern resonance’s center. On the other hand, if Neptune’s migration takes ˜300 Myr, we expect ˜50% of this population to reside in dynamically fossilized orbits over ˜1 au closer to the Sun than the modern resonance. We highlight 2015 KH162 as a likely member of this fossilized 3:1 population. Under any plausible migration scenario, nearly all high-perihelion objects in resonances beyond the 4:1 MMR (near 76 au) reach their orbits well after Neptune stops migrating and compose a recently generated, dynamically active population.

  6. The social distraction of facial paralysis: Objective measurement of social attention using eye-tracking.

    Science.gov (United States)

    Ishii, Lisa; Dey, Jacob; Boahene, Kofi D O; Byrne, Patrick J; Ishii, Masaru

    2016-02-01

    To measure the attentional distraction to the facial paralysis deformity using eye-tracking, and to distinguish between attention paid to the upper and lower facial divisions in patients with complete paralysis. We hypothesized that features affected by the paralysis deformity would distract the casual observer, leading to an altered pattern of facial attention as compared to normals. Randomized controlled experiment. Sixty casual observers viewed images of paralyzed faces (House-Brackmann [HB] IV-VI) and normal faces smiling and in repose. The SMI iView X RED (SensoMotoric, Inc., Boston, MA) eye-gaze tracker recorded eye movements of observers gazing on the faces. Fixation durations for predefined areas of interest were analyzed using three separate multivariate analyses. Casual observers gazing on both paralyzed and normal faces directed the majority of their attention to the central triangle (CT) region. Significant differences occurred in the distribution of attention among individual features in the CT and to individual sides of the face. Observers directed more attention to the mouth of paralyzed faces, smiling (analysis of variance [ANOVA] > F 0.0001) and in repose (ANOVA > F 0.0000). Attention was asymmetrically distributed between the two halves of paralyzed faces (paralyzed smiling minus normal smiling P > |z| 0.000). Casual observers directed attention in a measurably different way when gazing on paralyzed faces as compared to normal faces, a finding exacerbated with smiling. These findings help explain society's perceptions of attractiveness and affect display that differ for paralyzed and normal faces and can be used to direct our reconstructive efforts. N/A. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

  7. Klet Observatory – European Contribution to Detecting and Tracking of Near Earth Objects

    Directory of Open Access Journals (Sweden)

    Milos Tichy

    2012-03-01

    Full Text Available Near Earth Object (NEO research is an expanding field of astronomy. Is is important for solar system science and also for protecting human society from asteroid and comet hazard.  A near-Earth object (NEO can be defined as an asteroid or comet that has a possibility of making an approach to the Earth, or possibly even collide with it. The discovery rate of current NEO surveys reflects progressive improvement in a number of technical areas. An integral part of NEO discovery is astrometric follow-up fundamental for precise orbit computation and for the reasonable judging of future close encounters with the Earth including possible impact solutions. A wide international cooperation is fundamental for NEO research.  The Klet Observatory (South Bohemia, Czech Republic is aimed especially at the confirmation, early follow-up, long-arc follow-up and recovery of Near Earth Objects. It ranks among the world´s most prolific professional NEO follow-up programmes.  The first NEO follow-up programme started at Klet in 1993 using 0.57-reflector equipped with a small CCD camera. A fundamental upgrade was made in 2002 when the 1.06-m KLENOT telescope was put into regular operation. The KLENOT Telescope is the largest telescope in Europe used exclusively for observations of minor planets (asteroids and comets and full observing time is dedicated to the KLENOT team.  Equipment, technology, software, observing strategy and results of both the Klet Observatory NEO Project between 1993-2010 and the first phase of the KLENOT Project from March 2002 to September 2008 are presented. They consist of thousands of precise astrometric measurements of Near Earth Objects and also three newly discovered Near Earth Asteroids.  Klet Observatory NEO activities as well as our future plans fully reflect international strategies and cooperation in the field of NEO studies.

  8. Track-Before-Detect Algorithm for Faint Moving Objects based on Random Sampling and Consensus

    Science.gov (United States)

    2014-09-01

    Vehicles Richard Rast and Waid Schlaegel AFRL, Directed Energy Vincent Schmidt AFRL, Human Effectiveness Directorate Stephen Gregory The Boeing...the data set collected with the RH 17-inch telescope, the night of 2014/10/02 UT, we evaluate the performance of RANSAC-MT by testing it using...calibration techniques. Moving object signatures of various intensities and angular velocities are tested . Figure 6 shows the results from one of the

  9. Robust Speed Tracking Control for a Micro Turbine as a Distributed Energy Resource via Feedback Domination and Disturbance Observer

    Directory of Open Access Journals (Sweden)

    Ancheng Xu

    2017-01-01

    Full Text Available Micro turbine (MT is characterized with complex dynamics, parameter uncertainties, and variable working conditions. In this paper, a novel robust controller is investigated for a single-shaft micro turbine as a distributed energy resource by integrating a feedback domination control technique and a feedforward disturbance compensation. An active estimation process of the mismatched disturbances is firstly enabled by constructing a disturbance observer. Secondly, we adopt a feedback domination technique, rather than popularly used feedback linearization methods, to handle the system nonlinearities. In an explicit way, the composite controllers are then derived by recursive design based on Lyapunov theory while a global input-to-state stability can be guaranteed. Abundant comparison simulation results are provided to demonstrate the effectiveness of the proposed scheme, which not only perform an improved closed-loop control performance comparing to all existing results, but also render a simple control law which will ease its practical implementation.

  10. Channel Characterization and Robust Tracking for Diversity Reception over Time-Variant Off-Body Wireless Communication Channels

    Science.gov (United States)

    Van Torre, Patrick; Vallozzi, Luigi; Rogier, Hendrik; Moeneclaey, Marc; Verhaevert, Jo

    2010-12-01

    In the 2.45 GHz band, indoor wireless off-body data communication by a moving person can be problematic due to time-variant signal fading and the consequent variation in channel parameters. Off-body communication specifically suffers from the combined effects of fading, shadowing, and path loss due to time-variant multipath propagation in combination with shadowing by the human body. Measurements are performed to analyze the autocorrelation, coherence time, and power spectral density for a person equipped with a wearable receive system moving at different speeds for different configurations and antenna positions. Diversity reception with multiple textile antennas integrated in the clothing provides a means of improving the reliability of the link. For the dynamic channel estimation, a scheme using hard decision feedback after MRC with adaptive low-pass filtering is demonstrated to be successful in providing robust data detection for long data bursts, in the presence of dramatic channel variation.

  11. A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

    Science.gov (United States)

    Wen, John T.; Kreutz, Kenneth; Bayard, David S.

    1988-01-01

    A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

  12. Objectivity

    CERN Document Server

    Daston, Lorraine

    2010-01-01

    Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a...

  13. Robust Adaptive PID Controller for a Class of Uncertain Nonlinear Systems: An Application for Speed Tracking Control of an SI Engine

    Directory of Open Access Journals (Sweden)

    Tossaporn Chamsai

    2015-01-01

    Full Text Available The sliding mode control (SMC technique with a first-order low-pass filter (LPF is incorporated with a new adaptive PID controller. It is proposed for tracking control of an uncertain nonlinear system. In the proposed control scheme, the adaptation law is able to update the PID controller online during the control process within a short period. The chattering phenomenon of the SMC can be alleviated by incorporation of a first-order LPF, while the robustness of the control system is similar to that of the sliding mode. In the closed-loop control analysis, the convergence condition in the reaching phase and the existence condition of the sliding mode were analyzed. The stability of the closed-loop control is guaranteed in the sense of Lyapunov’s direct method. The simulations and experimental applications of a speed tracking control of a spark ignition (SI engine via electronic throttle valve control architecture are provided to verify the effectiveness and the feasibility of the proposed control scheme.

  14. Healthy older observers show equivalent perceptual-cognitive training benefits to young adults for multiple object tracking

    Directory of Open Access Journals (Sweden)

    Isabelle eLegault

    2013-06-01

    Full Text Available The capacity to process complex dynamic scenes is of critical importance in real life. For instance, travelling through a crowd while avoiding collisions and maintaining orientation and good motor control requires fluent and continuous perceptual-cognitive processing. It is well documented that effects of healthy aging can influence perceptual-cognitive processes (Faubert, 2002 and that the efficiency of such processes can improve with training even for older adults (Richards et al., 2006. Here we assess the capacity of older observers to learn complex dynamic visual scenes by using the 3D-multiple object tracking speed threshold protocol (Faubert & Sidebottom, 2012. Results show that this capacity is significantly affected by healthy aging but that perceptual-cognitive training can significantly reduce age-related effects in older individuals, who show an identical learning function to younger healthy adults. Data support the notion that plasticity in healthy older persons is maintained for processing complex dynamic scenes.

  15. MO-FG-CAMPUS-TeP3-04: Deliverable Robust Optimization in IMPT Using Quadratic Objective Function

    Energy Technology Data Exchange (ETDEWEB)

    Shan, J; Liu, W; Bues, M; Schild, S [Mayo Clinic Arizona, Phoenix, AZ (United States)

    2016-06-15

    Purpose: To find and evaluate the way of applying deliverable MU constraints into robust spot intensity optimization in Intensity-Modulated- Proton-Therapy (IMPT) to prevent plan quality and robustness from degrading due to machine deliverable MU-constraints. Methods: Currently, the influence of the deliverable MU-constraints is retrospectively evaluated by post-processing immediately following optimization. In this study, we propose a new method based on the quasi-Newton-like L-BFGS-B algorithm with which we turn deliverable MU-constraints on and off alternatively during optimization. Seven patients with two different machine settings (small and large spot size) were planned with both conventional and new methods. For each patient, three kinds of plans were generated — conventional non-deliverable plan (plan A), conventional deliverable plan with post-processing (plan B), and new deliverable plan (plan C). We performed this study with both realistic (small) and artificial (large) deliverable MU-constraints. Results: With small minimum MU-constraints considered, new method achieved a slightly better plan quality than conventional method (D95% CTV normalized to the prescription dose: 0.994[0.992∼0.996] (Plan C) vs 0.992[0.986∼0.996] (Plan B)). With large minimum MU constraints considered, results show that the new method maintains plan quality while plan quality from the conventional method is degraded greatly (D95% CTV normalized to the prescription dose: 0.987[0.978∼0.994] (Plan C) vs 0.797[0.641∼1.000] (Plan B)). Meanwhile, plan robustness of these two method’s results is comparable. (For all 7 patients, CTV DVH band gap at D95% normalized to the prescription dose: 0.015[0.005∼0.043] (Plan C) vs 0.012[0.006∼0.038] (Plan B) with small MU-constraints and 0.019[0.009∼0.039] (Plan C) vs 0.030[0.015∼0.041] (Plan B) with large MU-constraints) Conclusion: Positive correlation has been found between plan quality degeneration and magnitude of

  16. Development of radiation hardened robot for nuclear facility - Development of real-time stereo object tracking system using the optical correlator

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Eun Soo; Lee, S. H.; Lee, J. S. [Kwangwoon University, Seoul (Korea)

    2000-03-01

    Object tracking, through Centroide method used in the KAERI-M1 Stereo Robot Vision System developed at Atomic Research Center, is too sensitive to target's light variation and because it has a fragility which can't reflect the surrounding background, the application in the actual condition is very limited. Also the correlation method can constitute a relatively stable object tracker in noise features but the digital calculation amount is too massive in image correlation so real time materialization is limited. So the development of Optical Correlation based on Stereo Object Tracking System using high speed optical information processing technique will put stable the real time stereo object tracking system and substantial atomic industrial stereo robot vision system to practical use. This research is about developing real time stereo object tracking algorithm using optical correlation system through the technique which can be applied to Atomic Research Center's KAERI-M1 Stereo Vision Robot which will be used in atomic facility remote operations. And revise the stereo disparity using real time optical correlation technique, and materializing the application of the stereo object tracking algorithm to KAERI-M1 Stereo Robot. 19 refs., 45 figs., 2 tabs. (Author)

  17. Robust Geometric Control of a Distillation Column

    DEFF Research Database (Denmark)

    Kymmel, Mogens; Andersen, Henrik Weisberg

    1987-01-01

    A frequency domain method, which makes it possible to adjust multivariable controllers with respect to both nominal performance and robustness, is presented. The basic idea in the approach is that the designer assigns objectives such as steady-state tracking, maximum resonance peaks, bandwidth, m...... is used to examine and improve geometric control of a binary distillation column....

  18. Methods for robustness programming

    NARCIS (Netherlands)

    Olieman, N.J.

    2008-01-01

    Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition

  19. The Female Advantage in Object Location Memory is Robust to Verbalizability and Mode of Presentation of Test Stimuli

    Science.gov (United States)

    Lejbak, Lisa; Vrbancic, Mirna; Crossley, Margaret

    2009-01-01

    This study extends Duff and Hampson's [Duff, S., & Hampson, E. (2001). A sex difference on a novel spatial working memory task in humans. "Brain and Cognition, 47," 470-493] finding of a sex-related difference in favor of females for an object location memory task. Twenty female and 20 male undergraduate students performed both manual and…

  20. Robust design of multiple trailing edge flaps for helicopter vibration reduction: A multi-objective bat algorithm approach

    Science.gov (United States)

    Mallick, Rajnish; Ganguli, Ranjan; Seetharama Bhat, M.

    2015-09-01

    The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.

  1. Near Real Time Detection and Tracking of the EYJAFJÖLL (iceland) Ash Cloud by the RST (robust Satellite Technique) Approach

    Science.gov (United States)

    Tramutoli, V.; Filizzola, C.; Marchese, F.; Paciello, R.; Pergola, N.; Sannazzaro, F.

    2010-12-01

    Volcanic ash clouds, besides to be an environmental issue, represent a serious problem for air traffic and an important economic threat for aviation companies. During the recent volcanic crisis due to the April-May 2010 eruption of Eyjafjöll (Iceland), ash clouds became a real problem for common citizens as well: during the first days of the eruption thousands of flights were cancelled disrupting hundred of thousands of passengers. Satellite remote sensing confirmed to be a crucial tool for monitoring this kind of events, spreading for thousands of kilometres with a very rapid space-time dynamics. Especially weather satellites, thanks to their high temporal resolution, may furnish a fundamental contribution, providing frequently updated information. However, in this particular case ash cloud was accompanied by a sudden and significant emission of water vapour, due to the ice melting of Eyjafjallajökull glacier, making satellite ash detection and discrimination very hard, especially in the first few days of the eruption, exactly when accurate information were mostly required in order to support emergency management. Among the satellite-based techniques for near real-time detection and tracking of ash clouds, the RST (Robust Satellite Technique) approach, formerly named RAT - Robust AVHRR Technique, has been long since proposed, demonstrating high performances both in terms of reliability and sensitivity. In this paper, results achieved by using RST-based detection schemes, applied during the Eyjafjöll eruption were presented. MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced and Visible Infrared Imager) records, with a temporal sampling of 15 minutes, were used applying a standard as well as an advanced RST configuration, which includes the use of SO2 absorption band together with TIR and MIR channels. Main outcomes, limits and possible future improvements were also discussed.

  2. Robust patella motion tracking using intensity-based 2D-3D registration on dynamic bi-plane fluoroscopy: towards quantitative assessment in MPFL reconstruction surgery

    Science.gov (United States)

    Otake, Yoshito; Esnault, Matthieu; Grupp, Robert; Kosugi, Shinichi; Sato, Yoshinobu

    2016-03-01

    The determination of in vivo motion of multiple-bones using dynamic fluoroscopic images and computed tomography (CT) is useful for post-operative assessment of orthopaedic surgeries such as medial patellofemoral ligament reconstruction. We propose a robust method to measure the 3D motion of multiple rigid objects with high accuracy using a series of bi-plane fluoroscopic images and a multi-resolution, intensity-based, 2D-3D registration. A Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimizer was used with a gradient correlation similarity metric. Four approaches to register three rigid objects (femur, tibia-fibula and patella) were implemented: 1) an individual bone approach registering one bone at a time, each with optimization of a six degrees of freedom (6DOF) parameter, 2) a sequential approach registering one bone at a time but using the previous bone results as the background in DRR generation, 3) a simultaneous approach registering all the bones together (18DOF) and 4) a combination of the sequential and the simultaneous approaches. These approaches were compared in experiments using simulated images generated from the CT of a healthy volunteer and measured fluoroscopic images. Over the 120 simulated frames of motion, the simultaneous approach showed improved registration accuracy compared to the individual approach: with less than 0.68mm root-mean-square error (RMSE) for translation and less than 1.12° RMSE for rotation. A robustness evaluation was conducted with 45 trials of a randomly perturbed initialization showed that the sequential approach improved robustness significantly (74% success rate) compared to the individual bone approach (34% success) for patella registration (femur and tibia-fibula registration had a 100% success rate with each approach).

  3. A Robust Programming Approach to Bi-objective Optimization Model in the Disaster Relief Logistics Response Phase

    Directory of Open Access Journals (Sweden)

    Mohsen Saffarian

    2015-05-01

    Full Text Available Accidents and natural disasters and crises coming out of them indicate the importance of an integrated planning to reduce their effected. Therefore, disaster relief logistics is one of the main activities in disaster management. In this paper, we study the response phase of the disaster management cycle and a bi-objective model has been developed for relief chain logistic in uncertainty condition including uncertainty in traveling time an also amount of demand in damaged areas. The proposed mathematical model has two objective functions. The first one is to minimize the sum of arrival times to damaged area multiplying by amount of demand and the second objective function is to maximize the minimum ratio of satisfied demands in total period in order to fairness in the distribution of goods. In the proposed model, the problem has been considered periodically and in order to solve the mathematical model, Global Criterion method has been used and a case study has been done at South Khorasan.

  4. Register indicators of physical endurance of biological objects when running a treadmill and swimming with weights using computer video markerless tracking

    Directory of Open Access Journals (Sweden)

    Datsenko A.V.

    2014-12-01

    Full Text Available Purpose: to study the use of video tracking to assess physical endurance and indicators of biological objects fatigue when running on a treadmill and swimming with the load. Material and methods. Physical endurance evaluated by test facilities for running on a treadmill and swimming with the load. As the object of the studies used laboratory rats. Results. For indicators of physical endurance biological objects isolated areas running track of treadmill and electrical stimulation site, when swimming on the total area of the container isolated subarea near the water surface. With video tracking performed computer timing of finding biological object in different zones of the treadmill and containers for swimming. On the basis of data on the time location rats in a given zone apparatus for running and swimming, obtained in the dynamics of the test of physical endurance, build a "fatigue curves", quantified changes in the indices of hard work, depending on the duration of its execution. Conclusion. Video tracking allows to define the execution of physical work to overflowing with loads of aerobic and mixed aerobic-anaerobic power, establish quantitative indicators of changes in the dynamics of biological objects operability testing with the construction of "fatigue curve" and objectively determine the times of occurrence in experimental animals exhaustion when fails to perform physical work.

  5. Video stimuli reduce object-directed imitation accuracy: a novel two-person motion-tracking approach

    Directory of Open Access Journals (Sweden)

    Arran T Reader

    2015-05-01

    Full Text Available Imitation is an important form of social behavior, and research has aimed to discover and explain the neural and kinematic aspects of imitation. However, much of this research has featured single participants imitating in response to pre-recorded video stimuli. This is in spite of findings that show reduced neural activation to video versus real life movement stimuli, particularly in the motor cortex. We investigated the degree to which video stimuli may affect the imitation process using a novel motion tracking paradigm with high spatial and temporal resolution. We recorded 14 positions on the hands, arms, and heads of two individuals in an imitation experiment. One individual freely moved within given parameters (moving balls across a series of pegs and a second participant imitated. This task was performed with either simple (one ball or complex (three balls movement difficulty, and either face-to-face or via a live video projection. After an exploratory analysis, three dependent variables were chosen for examination: 3D grip position, joint angles in the arm, and grip aperture. A cross-correlation and multivariate analysis revealed that object-directed imitation task accuracy (as represented by grip position was reduced in video compared to face-to-face feedback, and in complex compared to simple difficulty. This was most prevalent in the left-right and forward-back motions, relevant to the imitator sitting face-to-face with the actor or with a live projected video of the same actor. The results suggest that for tasks which require object-directed imitation, video stimuli may not be an ecologically valid way to present task materials. However, no similar effects were found in the joint angle and grip aperture variables, suggesting that there are limits to the influence of video stimuli on imitation. The implications of these results are discussed with regards to previous findings, and with suggestions for future experimentation.

  6. Robust factorization

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Fisker, Rune; Åström, Kalle

    2002-01-01

    Factorization algorithms for recovering structure and motion from an image stream have many advantages, but they usually require a set of well-tracked features. Such a set is in generally not available in practical applications. There is thus a need for making factorization algorithms deal...... effectively with errors in the tracked features. We propose a new and computationally efficient algorithm for applying an arbitrary error function in the factorization scheme. This algorithm enables the use of robust statistical techniques and arbitrary noise models for the individual features....... These techniques and models enable the factorization scheme to deal effectively with mismatched features, missing features, and noise on the individual features. The proposed approach further includes a new method for Euclidean reconstruction that significantly improves convergence of the factorization algorithms...

  7. A feasibility study on the implementation of satellite-to-satellite tracking around a small near-Earth object

    Science.gov (United States)

    Church, Christopher J.

    Near-earth objects (NEOs) are asteroids and comets that have a perihelion distance of less than 1.3 astronomical units (AU). There are currently more than 10,000 known NEOs. The majority of these objects are less than 1 km in diameter. Despite the number of NEOs, little is known about most of them. Characterizing these objects is a crucial component in developing a thorough understanding of solar system evolution, human exploration, exploitation of asteroid resources, and threat mitigation. Of particular interest is characterizing the internal structure of NEOs. While ground-based methods exist for characterizing the internal structure of NEOs, the information that can be gleaned from such studies is limited and often accompanied by large uncertainty. An alternative is to use in situ studies to examine an NEO's shape and gravity field, which can be used to assess its internal structure. This thesis investigates the use of satellite-to-satellite tracking (SST) to map the gravity field of a small NEO on the order of 500 m or less. An analysis of the mission requirements of two previously flown SST missions, GRACE and GRAIL, is conducted. Additionally, a simulation is developed to investigate the dynamics of SST in the vicinity of a small NEO. This simulation is then used to simulate range and range-rate data in the strongly perturbed environment of the small NEO. These data are used in conjunction with the analysis of the GRACE and GRAIL missions to establish a range of orbital parameters that can be used to execute a SST mission around a small NEO. Preliminary mission requirements for data collection and orbital correction maneuvers are also established. Additionally, the data are used to determine whether or not proven technology can be used to resolve the expected range and range-rate measurements. It is determined that the orbit semi-major axis for each spacecraft should be approximately 100% to 200% of the NEO's mean diameter and the two spacecraft should be in

  8. Persistent Aerial Tracking system for UAVs

    KAUST Repository

    Mueller, Matthias

    2016-12-19

    In this paper, we propose a persistent, robust and autonomous object tracking system for unmanned aerial vehicles (UAVs) called Persistent Aerial Tracking (PAT). A computer vision and control strategy is applied to a diverse set of moving objects (e.g. humans, animals, cars, boats, etc.) integrating multiple UAVs with a stabilized RGB camera. A novel strategy is employed to successfully track objects over a long period, by ‘handing over the camera’ from one UAV to another. We evaluate several state-of-the-art trackers on the VIVID aerial video dataset and additional sequences that are specifically tailored to low altitude UAV target tracking. Based on the evaluation, we select the leading tracker and improve upon it by optimizing for both speed and performance, integrate the complete system into an off-the-shelf UAV, and obtain promising results showing the robustness of our solution in real-world aerial scenarios.

  9. More Evidence for Three Types of Cognitive Style: Validating the Object?Spatial Imagery and Verbal Questionnaire Using Eye Tracking when Learning with Texts and Pictures

    OpenAIRE

    H?ffler, Tim N.; Ko??Januchta, Marta; Leutner, Detlev

    2016-01-01

    Summary There is some indication that people differ regarding their visual and verbal cognitive style. The Object?Spatial Imagery and Verbal Questionnaire (OSIVQ) assumes a three?dimensional cognitive style model, which distinguishes between object imagery, spatial imagery and verbal dimensions. Using eye tracking as a means to observe actual gaze behaviours when learning with text?picture combinations, the current study aims to validate this three?dimensional assumption by linking the OSIVQ ...

  10. A constellation of SmallSats with synthetic tracking cameras to search for 90% of potentially hazardous near-Earth objects

    Science.gov (United States)

    Shao, Michael; Turyshev, Slava G.; Spangelo, Sara; Werne, Thomas; Zhai, Chengxing

    2017-07-01

    We present a new space mission concept that is capable of finding, detecting, and tracking 90% of near-Earth objects (NEO) with H magnitude of H ≤ 22 (i.e., 140 m in size) that are potentially hazardous to the Earth. The new mission concept relies on two emerging technologies: the technique of synthetic tracking and the new generation of small and capable interplanetary spacecraft. Synthetic tracking is a technique that de-streaks asteroid images by taking multiple fast exposures. With synthetic tracking, an 800 s observation with a 10 cm telescope in space can detect a moving object with apparent magnitude of 20.5 without losing sensitivity from streaking. We refer to NEOs with a minimum orbit intersection distance of constellation of six SmallSats (comparable in size to 9U CubeSats) equipped with 10 cm synthetic tracking cameras and evenly-distributed in 1.0 au heliocentric orbit could detect 90% of EGs with H ≤ 22 mag in 3.8 yr of observing time. A more advanced constellation of nine 20 cm telescopes could detect 90% of H = 24.2 mag (i.e., 50 m in size) EGs in less than 5 yr.

  11. Autonomous search and tracking of objects using model predictive control of unmanned aerial vehicle and gimbal: Hardware-in-the-loop simulation of payload and avionics

    OpenAIRE

    Skjong, Espen; Nundal, Stian Aa.; Leira, Frederik Stendahl; JOHANSEN, Tor Arne

    2015-01-01

    This paper describes the design of model predictive control (MPC) for an unmanned aerial vehicle (UAV) used to track objects of interest identified by a real-time camera vision (CV) module in a search and track (SAT) autonomous system. A fully functional UAV payload is introduced, which includes an infra-red (IR) camera installed in a two-axis gimbal system. Hardware-in-loop (HIL) simulations are performed to test the MPC's performance in the SAT system, where the gimbal attitude and the UAV'...

  12. Multi-Criteria Assessment of Spatial Robust Water Resource Vulnerability Using the TOPSIS Method Coupled with Objective and Subjective Weights in the Han River Basin

    Directory of Open Access Journals (Sweden)

    Eun-Sung Chung

    2016-12-01

    Full Text Available This study developed a multi-criteria approach to spatially assess the robust water resource vulnerability in sub-basins and applied it to the Han River basin. The Intergovernmental Panel on Climate Change (IPCC suggested three factors of vulnerability; namely, exposure, sensitivity and adaptive capacity were used in this study with respect to water quantity and quality. In this study, 16 water quantity indicators and 13 water quality indicators were selected to identify the vulnerability using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS method. Environmental and socioeconomic data were obtained from the national statistics database, and hydrological data were simulated using the calibrated Soil and Water Assessment Tool (SWAT model. Expert surveys and Shannon entropy method were used to determine subjective and objective weights for all indicators, individually. As a result, water quantity-vulnerable sub-basins were associated with high water use and water leakage ratios. Water quality-vulnerable sub-basins were associated with relatively high values of maximum consecutive dry days and heatwave days. The water quantity indices of both weighting methods showed relatively similar spatial distributions, while the distribution of water quality indices was distinct. These results suggest that considering different weighting methods is important for assessing the robust water resource vulnerability of sub-basins.

  13. Tool position tracking control of a nonlinear uncertain flexible robot ...

    Indian Academy of Sciences (India)

    tion results are presented to validate the effectiveness of the proposed controller like robustness and ... this research, tracking of tool position and minimization of motor torque are selected as the main objectives. In order to ..... In this research, the purpose is to design a suitable control which guarantees robust performance.

  14. Fast Compressive Tracking.

    Science.gov (United States)

    Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

    2014-10-01

    It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

  15. Novel Texture-based Probabilistic Object Recognition and Tracking Techniques for Food Intake Analysis and Traffic Monitoring

    Science.gov (United States)

    2015-10-02

    tiled regions over the object of interest. In 2011, [34] modeled objects as a collection of patches with a separate layer of global properties/motions...handle near passes and similar objects. Many good nonrigid object trackers such as [34] use tiled patches with color histogram features to model objects...Chatterjee. Classification of textures using gaussian markov random fields. Acoustics , Speech and Signal Processing, IEEE Transactions on, 33(4):959–963

  16. Technical Note: Combination of multiple EPID imager layers improves image quality and tracking performance of low contrast-to-noise objects.

    Science.gov (United States)

    Yip, Stephen S F; Rottmann, Joerg; Chen, Haijian; Morf, Daniel; Füglistaller, Rony; Star-Lack, Josh; Zentai, George; Berbeco, Ross

    2017-09-01

    We hypothesized that combining multiple amorphous silicon flat panel layers increases photon detection efficiency in an electronic portal imaging device (EPID), improving image quality and tracking accuracy of low-contrast targets during radiotherapy. The prototype imager evaluated in this study contained four individually programmable layers each with a copper converter layer, Gd 2 O 2 S scintillator, and active-matrix flat panel imager (AMFPI). The imager was placed on a Varian TrueBeam linac and a Las Vegas phantom programmed with sinusoidal motion (peak-to-peak amplitude = 20 mm, period = 3.5 s) was imaged at a frame rate of 10 Hz with one to four layers activated. Number of visible circles and CNR of least visible circle (depth = 0.5 mm, diameter = 7 mm) was computed to assess the image quality of single and multiple layers. A previously validated tracking algorithm was employed for auto-tracking. Tracking error was defined as the difference between the programmed and tracked positions of the circle. Pearson correlation coefficient (R) of CNR and tracking errors was computed. Motion-induced blurring significantly reduced circle visibility. During four cycles of phantom motion, the number of visible circles varied from 11-23, 13-24, 15-25, and 16-26 for one-, two-, three-, and four-layer imagers, respectively. Compared with using only a single layer, combining two, three, and four layers increased the median CNR by factors of 1.19, 1.42, and 1.71, respectively and reduced the average tracking error from 3.32 mm to 1.67 mm to 1.47 mm, and 0.74 mm, respectively. Significant correlations (P~10 -9 ) were found between the tracking error and CNR. Combination of four conventional EPID layers significantly improves the EPID image quality and tracking accuracy for a poorly visible object which is moving with a frequency and amplitude similar to respiratory motion. © 2017 American Association of Physicists in Medicine.

  17. A Real-Time Method to Detect and Track Moving Objects (DATMO from Unmanned Aerial Vehicles (UAVs Using a Single Camera

    Directory of Open Access Journals (Sweden)

    Bruce MacDonald

    2012-04-01

    Full Text Available We develop a real-time method to detect and track moving objects (DATMO from unmanned aerial vehicles (UAVs using a single camera. To address the challenging characteristics of these vehicles, such as continuous unrestricted pose variation and low-frequency vibrations, new approaches must be developed. The main concept proposed in this work is to create an artificial optical flow field by estimating the camera motion between two subsequent video frames. The core of the methodology consists of comparing this artificial flow with the real optical flow directly calculated from the video feed. The motion of the UAV between frames is estimated with available parallel tracking and mapping techniques that identify good static features in the images and follow them between frames. By comparing the two optical flows, a list of dynamic pixels is obtained and then grouped into dynamic objects. Tracking these dynamic objects through time and space provides a filtering procedure to eliminate spurious events and misdetections. The algorithms have been tested with a quadrotor platform using a commercial camera.

  18. Ionospheric errors at L-band for satellite and re-entry object tracking in the new equatorial-anomaly region

    Energy Technology Data Exchange (ETDEWEB)

    Pakula, W.A.; Klobuchar, J.A.; Anderson, D.N.; Doherty, P.H.

    1990-05-03

    The ionosphere can significantly limit the accuracy of precise tracking of satellites and re-entry objects, especially in the equatorial anomaly region of the world where the electron density is the highest. The determine typical changes induced by the ionosphere, the Fully Analytic Ionospheric Model, (FAIM), was used to model range and range-rate errors over Kwajalein Island, located near the equatorial anomaly region in the Pacific. Model results show that range-rate errors of up to one foot per second can occur at L-band for certain, near-vertical re-entry object trajectories during high solar activity daytime conditions.

  19. Operations of a non-stellar object tracker in space

    DEFF Research Database (Denmark)

    Riis, Troels; Jørgensen, John Leif; Betto, Maurizio

    1999-01-01

    The ability to detect and track non-stellar objects by utilizing a star tracker may seem rather straight forward, as any bright object, not recognized as a star by the system is a non stellar object. However, several pitfalls and errors exist, if a reliable and robust detection is required. To te...

  20. Adaptive learning compressive tracking based on Markov location prediction

    Science.gov (United States)

    Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

    2017-03-01

    Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

  1. More Evidence for Three Types of Cognitive Style: Validating the Object-Spatial Imagery and Verbal Questionnaire Using Eye Tracking when Learning with Texts and Pictures.

    Science.gov (United States)

    Höffler, Tim N; Koć-Januchta, Marta; Leutner, Detlev

    2017-01-01

    There is some indication that people differ regarding their visual and verbal cognitive style. The Object-Spatial Imagery and Verbal Questionnaire (OSIVQ) assumes a three-dimensional cognitive style model, which distinguishes between object imagery, spatial imagery and verbal dimensions. Using eye tracking as a means to observe actual gaze behaviours when learning with text-picture combinations, the current study aims to validate this three-dimensional assumption by linking the OSIVQ to learning behaviour. The results largely confirm the model in that they show the expected correlations between results on the OSIVQ, visuo-spatial ability and learning behaviour. Distinct differences between object visualizers, spatial visualizers and verbalizers could be demonstrated. © 2016 The Authors Published by John Wiley & Sons Ltd.

  2. Assessing computerized eye tracking technology for gaining insight into expert interpretation of the 12-lead electrocardiogram: an objective quantitative approach.

    Science.gov (United States)

    Bond, R R; Zhu, T; Finlay, D D; Drew, B; Kligfield, P D; Guldenring, D; Breen, C; Gallagher, A G; Daly, M J; Clifford, G D

    2014-01-01

    It is well known that accurate interpretation of the 12-lead electrocardiogram (ECG) requires a high degree of skill. There is also a moderate degree of variability among those who interpret the ECG. While this is the case, there are no best practice guidelines for the actual ECG interpretation process. Hence, this study adopts computerized eye tracking technology to investigate whether eye-gaze can be used to gain a deeper insight into how expert annotators interpret the ECG. Annotators were recruited in San Jose, California at the 2013 International Society of Computerised Electrocardiology (ISCE). Each annotator was recruited to interpret a number of 12-lead ECGs (N=12) while their eye gaze was recorded using a Tobii X60 eye tracker. The device is based on corneal reflection and is non-intrusive. With a sampling rate of 60Hz, eye gaze coordinates were acquired every 16.7ms. Fixations were determined using a predefined computerized classification algorithm, which was then used to generate heat maps of where the annotators looked. The ECGs used in this study form four groups (3=ST elevation myocardial infarction [STEMI], 3=hypertrophy, 3=arrhythmias and 3=exhibiting unique artefacts). There was also an equal distribution of difficulty levels (3=easy to interpret, 3=average and 3=difficult). ECGs were displayed using the 4x3+1 display format and computerized annotations were concealed. Precisely 252 expert ECG interpretations (21 annotators×12 ECGs) were recorded. Average duration for ECG interpretation was 58s (SD=23). Fleiss' generalized kappa coefficient (Pa=0.56) indicated a moderate inter-rater reliability among the annotators. There was a 79% inter-rater agreement for STEMI cases, 71% agreement for arrhythmia cases, 65% for the lead misplacement and dextrocardia cases and only 37% agreement for the hypertrophy cases. In analyzing the total fixation duration, it was found that on average annotators study lead V1 the most (4.29s), followed by leads V2 (3.83s

  3. Development and Application of an Objective Tracking Algorithm for Tropical Cyclones over the North-West Pacific purely based on Wind Speeds

    Science.gov (United States)

    Befort, Daniel J.; Kruschke, Tim; Leckebusch, Gregor C.

    2017-04-01

    Tropical Cyclones over East Asia have huge socio-economic impacts due to their strong wind fields and large rainfall amounts. Especially, the most severe events are associated with huge economic losses, e.g. Typhoon Herb in 1996 is related to overall losses exceeding 5 billion US (Munich Re, 2016). In this study, an objective tracking algorithm is applied to JRA55 reanalysis data from 1979 to 2014 over the Western North Pacific. For this purpose, a purely wind based algorithm, formerly used to identify extra-tropical wind storms, has been further developed. The algorithm is based on the exceedance of the local 98th percentile to define strong wind fields in gridded climate data. To be detected as a tropical cyclone candidate, the following criteria must be fulfilled: 1) the wind storm must exist for at least eight 6-hourly time steps and 2) the wind field must exceed a minimum size of 130.000km2 for each time step. The usage of wind information is motivated to focus on damage related events, however, a pre-selection based on the affected region is necessary to remove events of extra-tropical nature. Using IBTrACS Best Tracks for validation, it is found that about 62% of all detected tropical cyclone events in JRA55 reanalysis can be matched to an observed best track. As expected the relative amount of matched tracks increases with the wind intensity of the event, with a hit rate of about 98% for Violent Typhoons, above 90% for Very Strong Typhoons and about 75% for Typhoons. Overall these results are encouraging as the parameters used to detect tropical cyclones in JRA55, e.g. minimum area, are also suitable to detect TCs in most CMIP5 simulations and will thus allow estimates of potential future changes.

  4. Robust Vertex Fitters

    CERN Document Server

    Speer, Thomas; Vanlaer, Pascal; Waltenberger, Wolfgang

    2005-01-01

    While linear least-square estimators are optimal when the model is linear and all random noise is Gaussian, they are very sensitive to outlying tracks. Non-linear vertex reconstruction algorithms offer a higher degree of robustness against such outliers Two of the algorithms presented, the Adaptive filter and the Trimmed Kalman filter are able to down-weight or discard these outlying tracks, while a third, the Gaussian-sum filter, offers a better treatment of non-Gaussian distributions of track parameter errors when these are modelled by Gaussian mixtures.

  5. Pupil size signals mental effort deployed during multiple object tracking and predicts brain activity in the dorsal attention network and the locus coeruleus.

    Science.gov (United States)

    Alnæs, Dag; Sneve, Markus Handal; Espeseth, Thomas; Endestad, Tor; van de Pavert, Steven Harry Pieter; Laeng, Bruno

    2014-04-01

    Attentional effort relates to the allocation of limited-capacity attentional resources to meet current task demands and involves the activation of top-down attentional systems in the brain. Pupillometry is a sensitive measure of this intensity aspect of top-down attentional control. Studies relate pupillary changes in response to cognitive processing to activity in the locus coeruleus (LC), which is the main hub of the brain's noradrenergic system and it is thought to modulate the operations of the brain's attentional systems. In the present study, participants performed a visual divided attention task known as multiple object tracking (MOT) while their pupil sizes were recorded by use of an infrared eye tracker and then were tested again with the same paradigm while brain activity was recorded using fMRI. We hypothesized that the individual pupil dilations, as an index of individual differences in mental effort, as originally proposed by Kahneman (1973), would be a better predictor of LC activity than the number of tracked objects during MOT. The current results support our hypothesis, since we observed pupil-related activity in the LC. Moreover, the changes in the pupil correlated with activity in the superior colliculus and the right thalamus, as well as cortical activity in the dorsal attention network, which previous studies have shown to be strongly activated during visual tracking of multiple targets. Follow-up pupillometric analyses of the MOT task in the same individuals also revealed that individual differences to cognitive load can be remarkably stable over a lag of several years. To our knowledge this is the first study using pupil dilations as an index of attentional effort in the MOT task and also relating these to functional changes in the brain that directly implicate the LC-NE system in the allocation of processing resources.

  6. Object Individuation or Object Movement as Attractor? A Replication of the Wide-Screen/Narrow-Screen Study by Means of (a Standard Looking Time Methodology and (b Eye Tracking

    Directory of Open Access Journals (Sweden)

    Peter Krøjgaard

    2013-01-01

    Full Text Available We report a replication experiment of a mechanized version of the seminal wide-screen/narrow-screen design of Wilcox and Baillargeon (1998 with 9.5-month-old infants (N=80. Two different methodologies were employed simultaneously: (a the standard looking time paradigm and (b eye tracking. Across conditions with three different screen sizes, the results from both methodologies revealed a clear and interesting pattern: the looking times increased as a significantly linear function of reduced screen sizes, that is, independently of the number of different objects involved. There was no indication in the data that the infants made use of the featural differences between the different-looking objects involved. The results suggest a simple, novel, and thought-provoking interpretation of the infants’ looking behavior in the wide-screen/narrow-screen design: moving objects are attractors, and the more space left for visible object movement in the visual field, the longer are infants’ looks. Consequently, no cognitive interpretation may be needed.

  7. Simulation of laser detection and ranging (LADAR) and forward-looking infrared (FLIR) data for autonomous tracking of airborne objects

    Science.gov (United States)

    Powell, Gavin; Markham, Keith C.; Marshall, David

    2000-06-01

    This paper presents the results of an investigation leading into an implementation of FLIR and LADAR data simulation for use in a multi sensor data fusion automated target recognition system. At present the main areas of application are in military environments but systems can easily be adapted to other areas such as security applications, robotics and autonomous cars. Recent developments have been away from traditional sensor modeling and toward modeling of features that are external to the system, such as atmosphere and part occlusion, to create a more realistic and rounded system. We have implemented such techniques and introduced a means of inserting these models into a highly detailed scene model to provide a rich data set for later processing. From our study and implementation we are able to embed sensor model components into a commercial graphics and animation package, along with object and terrain models, which can be easily used to create a more realistic sequence of images.

  8. The posture-based motion planning framework: new findings related to object manipulation, moving around obstacles, moving in three spatial dimensions, and haptic tracking.

    Science.gov (United States)

    Rosenbaum, David A; Cohen, Rajal G; Dawson, Amanda M; Jax, Steven A; Meulenbroek, Ruud G; van der Wel, Robrecht; Vaughan, Jonathan

    2009-01-01

    We describe the results of recent studies inspired by the posture-based motion planning theory (Rosenbaum et al., 2001). The research concerns analyses of human object manipulation, obstacle avoidance, three-dimensional movement generation, and haptic tracking, the findings of which are discussed in relation to whether they support or fail to support the premises of the theory. Each of the aforementioned topics potentially challenges the theory's claim that, in motion, goal postures are planned before the selection of movements towards those postures. However, even the quasi-continuous phenomena under study show features that comply with prospective, end-state-based motion planning. We conclude that progress in motor control should not be frustrated by the view that no model is, or will ever be, optimal. Instead, it should find promise in the steady growth of insights afforded by challenges to existing theories.

  9. High Dynamics and Precision Optical Measurement Using a Position Sensitive Detector (PSD in Reflection-Mode: Application to 2D Object Tracking over a Smart Surface

    Directory of Open Access Journals (Sweden)

    Ioan Alexandru Ivan

    2012-12-01

    Full Text Available When related to a single and good contrast object or a laser spot, position sensing, or sensitive, detectors (PSDs have a series of advantages over the classical camera sensors, including a good positioning accuracy for a fast response time and very simple signal conditioning circuits. To test the performance of this kind of sensor for microrobotics, we have made a comparative analysis between a precise but slow video camera and a custom-made fast PSD system applied to the tracking of a diffuse-reflectivity object transported by a pneumatic microconveyor called Smart-Surface. Until now, the fast system dynamics prevented the full control of the smart surface by visual servoing, unless using a very expensive high frame rate camera. We have built and tested a custom and low cost PSD-based embedded circuit, optically connected with a camera to a single objective by means of a beam splitter. A stroboscopic light source enhanced the resolution. The obtained results showed a good linearity and a fast (over 500 frames per second response time which will enable future closed-loop control by using PSD.

  10. An object-oriented modeling and simulation framework for bearings-only multi-target tracking using an unattended acoustic sensor network

    Science.gov (United States)

    Aslan, Murat Šamil

    2013-10-01

    Tracking ground targets using low cost ground-based sensors is a challenging field because of the limited capabilities of such sensors. Among the several candidates, including seismic and magnetic sensors, the acoustic sensors based on microphone arrays have a potential of being useful: They can provide a direction to the sound source, they can have a relatively better range, and the sound characteristics can provide a basis for target classification. However, there are still many problems. One of them is the difficulty to resolve multiple sound sources, another is that they do not provide distance, a third is the presence of background noise from wind, sea, rain, distant air and land traffic, people, etc., and a fourth is that the same target can sound very differently depending on factors like terrain type, topography, speed, gear, distance, etc. Use of sophisticated signal processing and data fusion algorithms is the key for compensating (to an extend) the limited capabilities and mentioned problems of these sensors. It is hard, if not impossible, to evaluate the performance of such complex algorithms analytically. For an effective evaluation, before performing expensive field trials, well-designed laboratory experiments and computer simulations are necessary. Along this line, in this paper, we present an object-oriented modeling and simulation framework which can be used to generate simulated data for the data fusion algorithms for tracking multiple on-road targets in an unattended acoustic sensor network. Each sensor node in the network is a circular microphone array which produces the direction of arrival (DOA) (or bearing) measurements of the targets and sends this information to a fusion center. We present the models for road networks, targets (motion and acoustic power) and acoustic sensors in an object-oriented fashion where different and possibly time-varying sampling periods for each sensor node is possible. Moreover, the sensor's signal processing and

  11. Siamese convolutional networks for tracking the spine motion

    Science.gov (United States)

    Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

    2017-09-01

    Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

  12. Object tracking mask-based NLUT on GPUs for real-time generation of holographic videos of three-dimensional scenes.

    Science.gov (United States)

    Kwon, M-W; Kim, S-C; Yoon, S-E; Ho, Y-S; Kim, E-S

    2015-02-09

    A new object tracking mask-based novel-look-up-table (OTM-NLUT) method is proposed and implemented on graphics-processing-units (GPUs) for real-time generation of holographic videos of three-dimensional (3-D) scenes. Since the proposed method is designed to be matched with software and memory structures of the GPU, the number of compute-unified-device-architecture (CUDA) kernel function calls and the computer-generated hologram (CGH) buffer size of the proposed method have been significantly reduced. It therefore results in a great increase of the computational speed of the proposed method and enables real-time generation of CGH patterns of 3-D scenes. Experimental results show that the proposed method can generate 31.1 frames of Fresnel CGH patterns with 1,920 × 1,080 pixels per second, on average, for three test 3-D video scenarios with 12,666 object points on three GPU boards of NVIDIA GTX TITAN, and confirm the feasibility of the proposed method in the practical application of electro-holographic 3-D displays.

  13. Object Tracking Through Adaptive Correlation

    Science.gov (United States)

    1992-12-17

    images used were those utilized by Capt. Law (10) which were provided by the Model-Based Vision Laboratory, WL/ AARA , Wright-Patterson AFB, Ohio. These...kilometers to 1 kilometer distance. The FLIR images were provided by the Model-Based Vision Laboratory (WL/ AARA ). The images provided were 499x320 pixels in...MONITORING Mr. Jim Leonard AGENCY REPORT NUMBER WL/ AARA , WPAFB, OH 45433 11. SUPPLEMENTARY NOTES 12a. DISTRIBUTION /AVAILABILITY STATEMENT 12b

  14. Doppler tracking

    Science.gov (United States)

    Thomas, Christopher Jacob

    This study addresses the development of a methodology using the Doppler Effect for high-resolution, short-range tracking of small projectiles and vehicles. Minimal impact on the design of the moving object is achieved by incorporating only a transmitter in it and using ground stations for all other components. This is particularly useful for tracking objects such as sports balls that have configurations and materials that are not conducive to housing onboard instrumentation. The methodology developed here uses four or more receivers to monitor a constant frequency signal emitted by the object. Efficient and accurate schemes for filtering the raw signals, determining the instantaneous frequencies, time synching the frequencies from each receiver, smoothing the synced frequencies, determining the relative velocity and radius of the object and solving the nonlinear system of equations for object position in three dimensions as a function of time are developed and described here.

  15. Robust real-time fault tracking for the 2011 Mw 9.0 Tohoku earthquake based on the phased-array-interference principle

    Science.gov (United States)

    Zhang, Yong; Wang, Rongjiang; Parolai, Stefano; Zschau, Jochen

    2013-04-01

    Based on the principle of the phased array interference, we have developed an Iterative Deconvolution Stacking (IDS) method for real-time kinematic source inversion using near-field strong-motion and GPS networks. In this method, the seismic and GPS stations work like an array radar. The whole potential fault area is scanned patch by patch by stacking the apparent source time functions, which are obtained through deconvolution between the recorded seismograms and synthetic Green's functions. Once some significant source signals are detected any when and where, their signatures are removed from the observed seismograms. The procedure is repeated until the accumulative seismic moment being found converges and the residual seismograms are reduced below the noise level. The new approach does not need any artificial constraint used in the source parameterization such as, for example, fixing the hypocentre, restricting the rupture velocity and rise time, etc. Thus, it can be used for automatic real-time source inversion. In the application to the 2011 Tohoku earthquake, the IDS method is proved to be robust and reliable on the fast estimation of moment magnitude, fault area, rupture direction, and maximum slip, etc. About at 100 s after the rupture initiation, we can get the information that the rupture mainly propagates along the up-dip direction and causes a maximum slip of 17 m, which is enough to release a tsunami early warning. About two minutes after the earthquake occurrence, the maximum slip is found to be 31 m, and the moment magnitude reaches Mw8.9 which is very close to the final moment magnitude (Mw9.0) of this earthquake.

  16. Incentives from Curriculum Tracking

    Science.gov (United States)

    Koerselman, Kristian

    2013-01-01

    Curriculum tracking creates incentives in the years before its start, and we should therefore expect test scores to be higher during those years. I find robust evidence for incentive effects of tracking in the UK based on the UK comprehensive school reform. Results from the Swedish comprehensive school reform are inconclusive. Internationally, I…

  17. Model-Based Real-Time Head Tracking

    Directory of Open Access Journals (Sweden)

    Ström Jacob

    2002-01-01

    Full Text Available This paper treats real-time tracking of a human head using an analysis by synthesis approach. The work is based on the Structure from Motion (SfM algorithm from Azarbayejani and Pentland (1995. We will analyze the convergence properties of the SfM algorithm for planar objects, and extend it to handle new points. The extended algorithm is then used for head tracking. The system tracks feature points in the image using a texture mapped three-dimensional model of the head. The texture is updated adaptively so that points in the ear region can be tracked when the user′s head is rotated far, allowing out-of-plane rotation of up to without losing track. The covariance of the - and the -coordinates are estimated and forwarded to the Kalman filter, making the tracker robust to occlusion. The system automatically detects tracking failure and reinitializes the algorithm using information gathered in the original initialization process.

  18. Tracking small targets in wide area motion imagery data

    Science.gov (United States)

    Mathew, Alex; Asari, Vijayan K.

    2013-03-01

    Object tracking in aerial imagery is of immense interest to the wide area surveillance community. In this paper, we propose a method to track very small targets such as pedestrians in AFRL Columbus Large Image Format (CLIF) Wide Area Motion Imagery (WAMI) data. Extremely small target sizes, combined with low frame rates and significant view changes, make tracking a very challenging task in WAMI data. Two problems should be tackled for object tracking frame registration and feature extraction. We employ SURF for frame registration. Although there are several feature extraction methods that work reasonably well when the scene is of high resolution, most methods fail when the resolution is very low. In our approach, we represent the target as a collection of intensity histograms and use a robust statistical distance to distinguish between the target and the background. We divide the object into m ×n regions and compute the normalized intensity histogram in each region to build a histogram matrix. The features can be compared using the histogram comparison techniques. For tracking, we use a combination of a bearing-only Kalman filter and the proposed feature extraction technique. The problem of template drift is solved by further localizing the target with a blob detection algorithm. The new template is taken as the detected blob. We show the robustness of the algorithm by giving a comparison of feature extraction part of our method with other feature extraction methods like SURF, SIFT and HoG and tracking part with mean-shift tracking.

  19. Objective evaluation of methods to track motion from clinical cardiac-gated tagged MRI without the use of a gold standard

    Science.gov (United States)

    Parages, Felipe M.; Denney, Thomas S.; Brankov, Jovan G.

    2015-03-01

    Cardiac-gated MRI is widely used for the task of measuring parameters related to heart motion. More specifically, gated tagged MRI is the preferred modality to estimate local deformation (strain) and rotational motion (twist) of myocardial tissue. Many methods have been proposed to estimate cardiac motion from gated MRI sequences. However, when dealing with clinical data, evaluation of these methods is problematic due to the absence of gold-standards for cardiac motion. To overcome that, a linear regression scheme known as regression-without-truth (RWT) was proposed in the past. RWT uses priors to model the distribution of true values, thus enabling us to assess image-analysis algorithms without knowledge of the ground-truth. Furthermore, it allows one to rank methods by means of an objective figure-of-merit γ (i.e. precision). In this work we apply RWT to compare the performance of several gated MRI motion-tracking methods (e.g. non-rigid registration, feature based, harmonic phase) at the task of estimating myocardial strain and left-ventricle (LV) twist, from a population of 18 clinical human cardiac-gated tagged MRI studies.

  20. Visual tracking of da Vinci instruments for laparoscopic surgery

    Science.gov (United States)

    Speidel, S.; Kuhn, E.; Bodenstedt, S.; Röhl, S.; Kenngott, H.; Müller-Stich, B.; Dillmann, R.

    2014-03-01

    Intraoperative tracking of laparoscopic instruments is a prerequisite to realize further assistance functions. Since endoscopic images are always available, this sensor input can be used to localize the instruments without special devices or robot kinematics. In this paper, we present an image-based markerless 3D tracking of different da Vinci instruments in near real-time without an explicit model. The method is based on different visual cues to segment the instrument tip, calculates a tip point and uses a multiple object particle filter for tracking. The accuracy and robustness is evaluated with in vivo data.

  1. Robustness Beamforming Algorithms

    Directory of Open Access Journals (Sweden)

    Sajad Dehghani

    2014-09-01

    Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

  2. Robustness Beamforming Algorithms

    Directory of Open Access Journals (Sweden)

    Sajad Dehghani

    2014-04-01

    Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

  3. Thermal Tracking of Sports Players

    DEFF Research Database (Denmark)

    Gade, Rikke; Moeslund, Thomas B.

    2014-01-01

    We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline...

  4. Detecting target changes in multiple object tracking with peripheral vision: More pronounced eccentricity effects for changes in form than in motion.

    Science.gov (United States)

    Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

    2017-05-01

    In the current study, dual-task performance is examined with multiple-object tracking as a primary task and target-change detection as a secondary task. The to-be-detected target changes in conditions of either change type (form vs. motion; Experiment 1) or change salience (stop vs. slowdown; Experiment 2), with changes occurring at either near (5°-10°) or far (15°-20°) eccentricities (Experiments 1 and 2). The aim of the study was to test whether changes can be detected solely with peripheral vision. By controlling for saccades and computing gaze distances, we could show that participants used peripheral vision to monitor the targets and, additionally, to perceive changes at both near and far eccentricities. Noticeably, gaze behavior was not affected by the actual target change. Detection rates as well as response times generally varied as a function of change condition and eccentricity, with faster detections for motion changes and near changes. However, in contrast to the effects found for motion changes, sharp declines in detection rates and increased response times were observed for form changes as a function of the eccentricities. This result can be ascribed to properties of the visual system, namely to the limited spatial acuity in the periphery and the comparably receptive motion sensitivity of peripheral vision. These findings show that peripheral vision is functional for simultaneous target monitoring and target-change detection as saccadic information suppression can be avoided and covert attention can be optimally distributed to all targets. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  5. The Near-Earth Asteroid Tracking (NEAT) Program: A Completely Automated System for Telescope Control, Wide-Field Imaging, and Object Detection

    Science.gov (United States)

    Pravdo, S. H.; Rabinowitz, D. L.; Helin, E. F.; Lawrence, K. J.; Bambery, R. J.; Clark, C. C.; Groom, S. L.; Levin, S.; Lorre, J.; Shaklan, S. B.; hide

    1998-01-01

    The Near-Earth Asteroid Tracking (NEAT) system operates autonomously at the Maui Space Surveillance Site on the summit of the extinct Haleakala Volcano Crater, Hawaii. The program began in December 1995 and continues with an observing run every month.

  6. DCS Budget Tracking System

    Data.gov (United States)

    Social Security Administration — DCS Budget Tracking System database contains budget information for the Information Technology budget and the 'Other Objects' budget. This data allows for monitoring...

  7. Neuromorphic Configurable Architecture for Robust Motion Estimation

    Directory of Open Access Journals (Sweden)

    Guillermo Botella

    2008-01-01

    Full Text Available The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM. This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.

  8. Multiple instance learning tracking method with local sparse representation

    KAUST Repository

    Xie, Chengjun

    2013-10-01

    When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them. To address this issue, in this study, the authors propose an online algorithm by combining multiple instance learning (MIL) and local sparse representation for tracking an object in a video system. The key idea in our method is to model the appearance of an object by local sparse codes that can be formed as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL learns the sparse codes by a classifier to discriminate the target from the background. Finally, results from the trained classifier are input into a particle filter framework to sequentially estimate the target state over time in visual tracking. In addition, to decrease the visual drift because of the accumulative errors when updating the dictionary and classifier, a two-step object tracking method combining a static MIL classifier with a dynamical MIL classifier is proposed. Experiments on some publicly available benchmarks of video sequences show that our proposed tracker is more robust and effective than others. © The Institution of Engineering and Technology 2013.

  9. Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state.

    Science.gov (United States)

    Dørum, Erlend S; Kaufmann, Tobias; Alnæs, Dag; Andreassen, Ole A; Richard, Geneviève; Kolskår, Knut K; Nordvik, Jan Egil; Westlye, Lars T

    2017-03-01

    Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. Here, based on the conception that the magnitude and characteristics of age-related differences in brain connectivity is dependent on cognitive context and effort, we tested the hypothesis that experimentally increasing cognitive load boosts the sensitivity to age and changes the discriminative network configurations. To this end, we obtained fMRI data from younger (n=25, mean age 24.16±5.11) and older (n=22, mean age 65.09±7.53) healthy adults during rest and two load levels of continuous multiple object tracking (MOT). Brain network nodes and their time-series were estimated using independent component analysis (ICA) and dual regression, and the edges in the brain networks were defined as the regularized partial temporal correlations between each of the node pairs at the individual level. Using machine learning based on a cross-validated regularized linear discriminant analysis (rLDA) we attempted to classify groups and cognitive load from the full set of edge-wise functional connectivity indices. While group classification using resting-state data was highly above chance (approx. 70% accuracy), functional connectivity (FC) obtained during MOT strongly increased classification performance, with 82% accuracy for the young and 95% accuracy for the old group at the highest load level. Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task

  10. Combination of multiple measurement cues for visual face tracking

    DEFF Research Database (Denmark)

    Katsarakis, Nikolaos; Pnevmatikakis, Aristodemos; Tan, Zheng-Hua

    2014-01-01

    Visual face tracking is an important building block for all intelligent living and working spaces, as it is able to locate persons without any human intervention or the need for the users to carry sensors on themselves. In this paper we present a novel face tracking system built on a particle...... filtering framework that facilitates the use of non-linear visual measurements on the facial area. We concentrate on three different such non-linear visual measurement cues, namely object detection, foreground segmentation and colour matching. We derive robust measurement likelihoods under a unified...... representation scheme and fuse them into our face tracking algorithm. This algorithm is complemented with optimum selection of the particle filter’s object model and a target handling scheme. The resulting face tracking system is extensively evaluated and compared to baseline ones....

  11. Real time eye tracking using Kalman extended spatio-temporal context learning

    Science.gov (United States)

    Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

    2017-06-01

    Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

  12. Robust human intrusion detection technique using hue-saturation histograms

    Science.gov (United States)

    Hassan, Waqas; Mitra, Bhargav; Bangalore, Nagachetan; Birch, Philip; Young, Rupert; Chatwin, Chris

    2011-04-01

    A robust human intrusion detection technique using hue-saturation histograms is presented in this paper. Initially a region of interest (ROI) is manually identified in the scene viewed by a single fixed CCTV camera. All objects in the ROI are automatically demarcated from the background using brightness and chromaticity distortion parameters. The segmented objects are then tracked using correlation between hue-saturation based bivariate distributions. The technique has been applied on all the 'Sterile Zone' sequences of the United Kingdom Home Office iLIDS dataset and its performance is evaluated with over 70% positive results.

  13. Robust surgery loading

    NARCIS (Netherlands)

    Hans, Elias W.; Wullink, Gerhard; van Houdenhoven, Mark; Kazemier, Geert

    2008-01-01

    We consider the robust surgery loading problem for a hospital’s operating theatre department, which concerns assigning surgeries and sufficient planned slack to operating room days. The objective is to maximize capacity utilization and minimize the risk of overtime, and thus cancelled patients. This

  14. Bewegingsvolgsysteem = Monitor tracking system

    NARCIS (Netherlands)

    Slycke, P.; Veltink, Petrus H.; Roetenberg, D.

    2006-01-01

    A motion tracking system for tracking an object composed of object parts in a three-dimensional space. The system comprises a number of magnetic field transmitters; a number of field receivers for receiving the magnetic fields of the field transmitters; a number of inertial measurement units for

  15. Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

    Science.gov (United States)

    Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

    2017-02-01

    Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

  16. Robust Affine Invariant Descriptors

    Directory of Open Access Journals (Sweden)

    Jianwei Yang

    2011-01-01

    Full Text Available An approach is developed for the extraction of affine invariant descriptors by cutting object into slices. Gray values associated with every pixel in each slice are summed up to construct affine invariant descriptors. As a result, these descriptors are very robust to additive noise. In order to establish slices of correspondence between an object and its affine transformed version, general contour (GC of the object is constructed by performing projection along lines with different polar angles. Consequently, affine in-variant division curves are derived. A slice is formed by points fall in the region enclosed by two adjacent division curves. To test and evaluate the proposed method, several experiments have been conducted. Experimental results show that the proposed method is very robust to noise.

  17. Location of a Missing Object and Detection of Its Absence by Infants: Contribution of an Eye-Tracking System to the Understanding of Infants' Strategies

    Science.gov (United States)

    Lecuyer, Roger; Berthereau, Sophie; Taieb, Amel Ben; Tardif, Nadia

    2004-01-01

    Previous research has demonstrated infants' capacity to discriminate between situations in which all the objects successively hidden behind a screen are present, or not, after the removal of the screen. Two types of interpretation have been proposed: counting capacity or object memorization capacity. In the usual paradigm, the missing object in…

  18. Slab track

    OpenAIRE

    Golob, Tina

    2014-01-01

    The last 160 years has been mostly used conventional track with ballasted bed, sleepers and steel rail. Ensuring the high speed rail traffic, increasing railway track capacities, providing comfortable and safe ride as well as high reliability and availability railway track, has led to development of innovative systems for railway track. The so-called slab track was first built in 1972 and since then, they have developed many different slab track systems around the world. Slab track was also b...

  19. Pixel-Level and Robust Vibration Source Sensing in High-Frame-Rate Video Analysis

    Directory of Open Access Journals (Sweden)

    Mingjun Jiang

    2016-11-01

    Full Text Available We investigate the effect of appearance variations on the detectability of vibration feature extraction with pixel-level digital filters for high-frame-rate videos. In particular, we consider robust vibrating object tracking, which is clearly different from conventional appearance-based object tracking with spatial pattern recognition in a high-quality image region of a certain size. For 512 × 512 videos of a rotating fan located at different positions and orientations and captured at 2000 frames per second with different lens settings, we verify how many pixels are extracted as vibrating regions with pixel-level digital filters. The effectiveness of dynamics-based vibration features is demonstrated by examining the robustness against changes in aperture size and the focal condition of the camera lens, the apparent size and orientation of the object being tracked, and its rotational frequency, as well as complexities and movements of background scenes. Tracking experiments for a flying multicopter with rotating propellers are also described to verify the robustness of localization under complex imaging conditions in outside scenarios.

  20. Pedestrian detection and tracking using a mixture of view-based shape-texture models

    NARCIS (Netherlands)

    Munder, S.; Schnörr, C.; Gavrila, D.M.

    2008-01-01

    This paper presents a robust multicue approach to the integrated detection and tracking of pedestrians in a cluttered urban environment. A novel spatiotemporal object representation is proposed, which combines a generative shape model and a discriminative texture classifier, both of which are

  1. The research and application of visual saliency and adaptive support vector machine in target tracking field.

    Science.gov (United States)

    Chen, Yuantao; Xu, Weihong; Kuang, Fangjun; Gao, Shangbing

    2013-01-01

    The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking's accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM). Furthermore, the paper's algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target's saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

  2. Coordinated Target Tracking via a Hybrid Optimization Approach

    Directory of Open Access Journals (Sweden)

    Yin Wang

    2017-02-01

    Full Text Available Recent advances in computer science and electronics have greatly expanded the capabilities of unmanned aerial vehicles (UAV in both defense and civil applications, such as moving ground object tracking. Due to the uncertainties of the application environments and objects’ motion, it is difficult to maintain the tracked object always within the sensor coverage area by using a single UAV. Hence, it is necessary to deploy a group of UAVs to improve the robustness of the tracking. This paper investigates the problem of tracking ground moving objects with a group of UAVs using gimbaled sensors under flight dynamic and collision-free constraints. The optimal cooperative tracking path planning problem is solved using an evolutionary optimization technique based on the framework of chemical reaction optimization (CRO. The efficiency of the proposed method was demonstrated through a series of comparative simulations. The results show that the cooperative tracking paths determined by the newly developed method allows for longer sensor coverage time under flight dynamic restrictions and safety conditions.

  3. Fixed Scan Area Tracking with Track Splitting Filtering Algorithm

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki

    2006-01-01

    The paper presents a simulation study by tracking multiple objects in a fixed window using a non deterministic scenario for the performance evaluation of track splitting algorithm on a digital signal processor.  Much of the previous work [1] was done on specific (deterministic) scenarios. One of ...... of such a tracking system by varying the density of the objects.  The track splitting algorithm using Kalman filters is implemented and a couple of tracking performance parameters are computed to investigate such randomly walking objects....

  4. INNER TRACKING

    CERN Multimedia

    P. Sharp

    The CMS Inner Tracking Detector continues to make good progress. The Objective for 2006 was to complete all of the CMS Tracker sub-detectors and to start the integration of the sub-detectors into the Tracker Support Tube (TST). The Objective for 2007 is to deliver to CMS a completed, installed, commissioned and calibrated Tracking System (Silicon Strip and Pixels) aligned to < 100µ in April 2008 ready for the first physics collisions at LHC. In November 2006 all of the sub-detectors had been delivered to the Tracker Integration facility (TIF) at CERN and the tests and QA procedures to be carried out on each sub-detector before integration had been established. In December 2006, TIB/TID+ was integrated into TOB+, TIB/TID- was being prepared for integration, and TEC+ was undergoing tests at the final tracker operating temperature (-100 C) in the Lyon cold room. In February 2007, TIB/TID- has been integrated into TOB-, and the installation of the pixel support tube and the services for TI...

  5. A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment

    Science.gov (United States)

    Cai, Lei; Wang, Lin; Li, Bo; Zhang, Libao; Lv, Wen

    2017-06-01

    Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

  6. Calculating track thrust with track functions

    Science.gov (United States)

    Chang, Hsi-Ming; Procura, Massimiliano; Thaler, Jesse; Waalewijn, Wouter J.

    2013-08-01

    In e+e- event shapes studies at LEP, two different measurements were sometimes performed: a “calorimetric” measurement using both charged and neutral particles and a “track-based” measurement using just charged particles. Whereas calorimetric measurements are infrared and collinear safe, and therefore calculable in perturbative QCD, track-based measurements necessarily depend on nonperturbative hadronization effects. On the other hand, track-based measurements typically have smaller experimental uncertainties. In this paper, we present the first calculation of the event shape “track thrust” and compare to measurements performed at ALEPH and DELPHI. This calculation is made possible through the recently developed formalism of track functions, which are nonperturbative objects describing how energetic partons fragment into charged hadrons. By incorporating track functions into soft-collinear effective theory, we calculate the distribution for track thrust with next-to-leading logarithmic resummation. Due to a partial cancellation between nonperturbative parameters, the distributions for calorimeter thrust and track thrust are remarkably similar, a feature also seen in LEP data.

  7. Adaptive hybrid likelihood model for visual tracking based on Gaussian particle filter

    Science.gov (United States)

    Wang, Yong; Tan, Yihua; Tian, Jinwen

    2010-07-01

    We present a new scheme based on multiple-cue integration for visual tracking within a Gaussian particle filter framework. The proposed method integrates the color, shape, and texture cues of an object to construct a hybrid likelihood model. During the measurement step, the likelihood model can be switched adaptively according to environmental changes, which improves the object representation to deal with the complex disturbances, such as appearance changes, partial occlusions, and significant clutter. Moreover, the confidence weights of the cues are adjusted online through the estimation using a particle filter, which ensures the tracking accuracy and reliability. Experiments are conducted on several real video sequences, and the results demonstrate that the proposed method can effectively track objects in complex scenarios. Compared with previous similar approaches through some quantitative and qualitative evaluations, the proposed method performs better in terms of tracking robustness and precision.

  8. Neonate turtle tracking data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The objectives of this project are to use novel satellite tracking methods to provide improved estimation of threats at foraging areas and along migration routes for...

  9. A Multi-Case Study of Research Using Mobile Imaging, Sensing and Tracking Technologies to Objectively Measure Behavior: Ethical Issues and Insights to Guide Responsible Research Practice

    Science.gov (United States)

    Nebeker, Camille; Linares-Orozco, Rubi; Crist, Katie

    Introduction: The increased availability of mobile sensing technologies is creating a paradigm shift for health research by creating new opportunities for measuring and monitoring behavior. For example, researchers can now collect objective information about a participant's daily activity using wearable devices that have: 1- Global Positioning…

  10. Thermal Tracking of Sports Players

    Directory of Open Access Journals (Sweden)

    Rikke Gade

    2014-07-01

    Full Text Available We present here a real-time tracking algorithm for thermal video from a sports game. Robust detection of people includes routines for handling occlusions and noise before tracking each detected person with a Kalman filter. This online tracking algorithm is compared with a state-of-the-art offline multi-target tracking algorithm. Experiments are performed on a manually annotated 2-minutes video sequence of a real soccer game. The Kalman filter shows a very promising result on this rather challenging sequence with a tracking accuracy above 70% and is superior compared with the offline tracking approach. Furthermore, the combined detection and tracking algorithm runs in real time at 33 fps, even with large image sizes of 1920 × 480 pixels.

  11. Orbit Determination Performance Improvements for High Area-to-Mass Ratio Space Object Tracking Using an Adaptive Gaussian Mixtures Estimation Algorithm

    Science.gov (United States)

    2009-07-01

    class of orbits, the set of quantities used in hypothesis generation for this work is taken to be: the geocentric range, the velocity magnitude along the...Given a hypothesized geocentric range, r, the inertial position of the object with respect to the geocenter is constructed by first forming the unit...Farinella and F. Mignard, “Solar radiation pressure perturbations for Earth satellites: I. A complete theory including penumbra transitions,” Astron

  12. A Robust Obstacle Avoidance for Service Robot Using Bayesian Approach

    Directory of Open Access Journals (Sweden)

    Widodo Budiharto

    2011-03-01

    Full Text Available The objective of this paper is to propose a robust obstacle avoidance method for service robot in indoor environment. The method for obstacles avoidance uses information about static obstacles on the landmark using edge detection. Speed and direction of people that walks as moving obstacle obtained by single camera using tracking and recognition system and distance measurement using 3 ultrasonic sensors. A new geometrical model and maneuvering method for moving obstacle avoidance introduced and combined with Bayesian approach for state estimation. The obstacle avoidance problem is formulated using decision theory, prior and posterior distribution and loss function to determine an optimal response based on inaccurate sensor data. Algorithms for moving obstacles avoidance method proposed and experiment results implemented to service robot also presented. Various experiments show that our proposed method very fast, robust and successfully implemented to service robot called Srikandi II that equipped with 4 DOF arm robot developed in our laboratory.

  13. Extending particle tracking capability with Delaunay triangulation.

    Science.gov (United States)

    Chen, Kejia; Anthony, Stephen M; Granick, Steve

    2014-04-29

    Particle tracking, the analysis of individual moving elements in time series of microscopic images, enables burgeoning new applications, but there is need to better resolve conformation and dynamics. Here we describe the advantages of Delaunay triangulation to extend the capabilities of particle tracking in three areas: (1) discriminating irregularly shaped objects, which allows one to track items other than point features; (2) combining time and space to better connect missing frames in trajectories; and (3) identifying shape backbone. To demonstrate the method, specific examples are given, involving analyzing the time-dependent molecular conformations of actin filaments and λ-DNA. The main limitation of this method, shared by all other clustering techniques, is the difficulty to separate objects when they are very close. This can be mitigated by inspecting locally to remove edges that are longer than their neighbors and also edges that link two objects, using methods described here, so that the combination of Delaunay triangulation with edge removal can be robustly applied to processing large data sets. As common software packages, both commercial and open source, can construct Delaunay triangulation on command, the methods described in this paper are both computationally efficient and easy to implement.

  14. PageRank tracker: from ranking to tracking.

    Science.gov (United States)

    Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

    2014-06-01

    Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

  15. Real-time markerless tracking for augmented reality: the virtual visual servoing framework.

    Science.gov (United States)

    Comport, Andrew I; Marchand, Eric; Pressigout, Muriel; Chaumette, François

    2006-01-01

    Tracking is a very important research subject in a real-time augmented reality context. The main requirements for trackers are high accuracy and little latency at a reasonable cost. In order to address these issues, a real-time, robust, and efficient 3D model-based tracking algorithm is proposed for a "video see through" monocular vision system. The tracking of objects in the scene amounts to calculating the pose between the camera and the objects. Virtual objects can then be projected into the scene using the pose. Here, nonlinear pose estimation is formulated by means of a virtual visual servoing approach. In this context, the derivation of point-to-curves interaction matrices are given for different 3D geometrical primitives including straight lines, circles, cylinders, and spheres. A local moving edges tracker is used in order to provide real-time tracking of points normal to the object contours. Robustness is obtained by integrating an M-estimator into the visual control law via an iteratively reweighted least squares implementation. This approach is then extended to address the 3D model-free augmented reality problem. The method presented in this paper has been validated on several complex image sequences including outdoor environments. Results show the method to be robust to occlusion, changes in illumination, and mistracking.

  16. Patch-based visual tracking with online representative sample selection

    Science.gov (United States)

    Ou, Weihua; Yuan, Di; Li, Donghao; Liu, Bin; Xia, Daoxun; Zeng, Wu

    2017-05-01

    Occlusion is one of the most challenging problems in visual object tracking. Recently, a lot of discriminative methods have been proposed to deal with this problem. For the discriminative methods, it is difficult to select the representative samples for the target template updating. In general, the holistic bounding boxes that contain tracked results are selected as the positive samples. However, when the objects are occluded, this simple strategy easily introduces the noises into the training data set and the target template and then leads the tracker to drift away from the target seriously. To address this problem, we propose a robust patch-based visual tracker with online representative sample selection. Different from previous works, we divide the object and the candidates into several patches uniformly and propose a score function to calculate the score of each patch independently. Then, the average score is adopted to determine the optimal candidate. Finally, we utilize the non-negative least square method to find the representative samples, which are used to update the target template. The experimental results on the object tracking benchmark 2013 and on the 13 challenging sequences show that the proposed method is robust to the occlusion and achieves promising results.

  17. Large scale tracking algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, Ross L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Love, Joshua Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melgaard, David Kennett [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Karelitz, David B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pitts, Todd Alan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zollweg, Joshua David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Anderson, Dylan Z. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nandy, Prabal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Whitlow, Gary L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bender, Daniel A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Byrne, Raymond Harry [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-01-01

    Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.

  18. The persistence of object file representations.

    Science.gov (United States)

    Noles, Nicholaus S; Scholl, Brian J; Mitroff, Stephen R

    2005-02-01

    Coherent visual experience of dynamic scenes requires not only that the visual system segment scenes into component objects but that these object representations persist, so that an object can be identified as the same object from an earlier time. Object files (OFs) are visual representations thought to mediate such abilities: OFs lie between lower level sensory processing and higher level recognition, and they track salient objects over time and motion. OFs have traditionally been studied via object-specific preview benefits (OSPBs), in which discriminations of an object's features are speeded when an earlier preview of those features occurred on the same object, as opposed to on a different object, beyond general displaywide priming. Despite its popularity, many fundamental aspects of the OF framework remain unexplored. For example, although OFs are thought to be involved primarily in online visual processing, we do not know how long such representations persist; previous studies found OSPBs for up to 1500 msec but did not test for longer durations. We explored this issue using a modified object reviewing paradigm and found that robust OSPBs persist for more than five times longer than has previously been tested-for at least 8 sec, and possibly for much longer. Object files may be the "glue" that makes visual experience coherent not just in online moment-by-moment processing, but on the scale of seconds that characterizes our everyday perceptual experiences. These findings also bear on research in infant cognition, where OFs are thought to explain infants' abilities to track and enumerate small sets of objects over longer durations.

  19. An Improved Fast Compressive Tracking Algorithm Based on Online Random Forest Classifier

    Directory of Open Access Journals (Sweden)

    Xiong Jintao

    2016-01-01

    Full Text Available The fast compressive tracking (FCT algorithm is a simple and efficient algorithm, which is proposed in recent years. But, it is difficult to deal with the factors such as occlusion, appearance changes, pose variation, etc in processing. The reasons are that, Firstly, even if the naive Bayes classifier is fast in training, it is not robust concerning the noise. Secondly, the parameters are required to vary with the unique environment for accurate tracking. In this paper, we propose an improved fast compressive tracking algorithm based on online random forest (FCT-ORF for robust visual tracking. Firstly, we combine ideas with the adaptive compressive sensing theory regarding the weighted random projection to exploit both local and discriminative information of the object. The second reason is the online random forest classifier for online tracking which is demonstrated with more robust to the noise adaptively and high computational efficiency. The experimental results show that the algorithm we have proposed has a better performance in the field of occlusion, appearance changes, and pose variation than the fast compressive tracking algorithm’s contribution.

  20. The Research and Application of Visual Saliency and Adaptive Support Vector Machine in Target Tracking Field

    Directory of Open Access Journals (Sweden)

    Yuantao Chen

    2013-01-01

    Full Text Available The efficient target tracking algorithm researches have become current research focus of intelligent robots. The main problems of target tracking process in mobile robot face environmental uncertainty. They are very difficult to estimate the target states, illumination change, target shape changes, complex backgrounds, and other factors and all affect the occlusion in tracking robustness. To further improve the target tracking’s accuracy and reliability, we present a novel target tracking algorithm to use visual saliency and adaptive support vector machine (ASVM. Furthermore, the paper’s algorithm has been based on the mixture saliency of image features. These features include color, brightness, and sport feature. The execution process used visual saliency features and those common characteristics have been expressed as the target’s saliency. Numerous experiments demonstrate the effectiveness and timeliness of the proposed target tracking algorithm in video sequences where the target objects undergo large changes in pose, scale, and illumination.

  1. Online Tracking

    Science.gov (United States)

    ... for other purposes, such as research, measurement, and fraud prevention. Mobile browsers work much like traditional web ... users’ Do Not Track preferences. Can I block online tracking? Consumers can learn about tracker-blocking browser ...

  2. Robust Nonlinear Control Based on Disturbance Observer for a Small-Scale Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Amir Razzaghian

    2017-09-01

    Full Text Available A robust nonlinear controller based on disturbance observer for the trajectory tracking control of a small-scale unmanned helicopter with nonlinear structure under external disturbances and parameter uncertainties is designed. The control objective is to let the helicopter track a predefined trajectory. The proposed robust nonlinear controller is based on the backstepping sliding mode control technique which combines both the capabilities of backstepping control and sliding mode control. The control performance developed based on a time-varying disturbance observer. In order to obtain an efficient control law design, the nonlinear model of the helicopter is reformulated as an affine nonlinear system. The mathematical proof using Lyapunov stability theorem shows that the closed loop system is asymptotically stable in the presence of this controller. To verify the robustness and stability of the proposed controller, it is compared with conventional sliding mode controller. The chattering phenomenon is attenuated significantly and the tracking error is also alleviated. The simulation results confirm the desirable performance of proposed robust nonlinear controller.

  3. Particle tracking

    CERN Document Server

    Safarík, K; Newby, J; Sørensen, P

    2002-01-01

    In this lecture we will present a short historical overview of different tracking detectors. Then we will describe currently used gaseous and silicon detectors and their performance. In the second part we will discuss how to estimate tracking precision, how to design a tracker and how the track finding works. After a short description of the LHC the main attention is drawn to the ALICE experiment since it is dedicated to study new states in hadronic matter at the LHC. The ALICE tracking procedure is discussed in detail. A comparison to the tracking in ATLAS, CMS and LHCb is given. (5 refs).

  4. Real-Time FPGA-Based Object Tracker with Automatic Pan-Tilt Features for Smart Video Surveillance Systems

    Directory of Open Access Journals (Sweden)

    Sanjay Singh

    2017-05-01

    Full Text Available The design of smart video surveillance systems is an active research field among the computer vision community because of their ability to perform automatic scene analysis by selecting and tracking the objects of interest. In this paper, we present the design and implementation of an FPGA-based standalone working prototype system for real-time tracking of an object of interest in live video streams for such systems. In addition to real-time tracking of the object of interest, the implemented system is also capable of providing purposive automatic camera movement (pan-tilt in the direction determined by movement of the tracked object. The complete system, including camera interface, DDR2 external memory interface controller, designed object tracking VLSI architecture, camera movement controller and display interface, has been implemented on the Xilinx ML510 (Virtex-5 FX130T FPGA Board. Our proposed, designed and implemented system robustly tracks the target object present in the scene in real time for standard PAL (720 × 576 resolution color video and automatically controls camera movement in the direction determined by the movement of the tracked object.

  5. Bilinear Approximate Model-Based Robust Lyapunov Control for Parabolic Distributed Collectors

    KAUST Repository

    Elmetennani, Shahrazed

    2016-11-09

    This brief addresses the control problem of distributed parabolic solar collectors in order to maintain the field outlet temperature around a desired level. The objective is to design an efficient controller to force the outlet fluid temperature to track a set reference despite the unpredictable varying working conditions. In this brief, a bilinear model-based robust Lyapunov control is proposed to achieve the control objectives with robustness to the environmental changes. The bilinear model is a reduced order approximate representation of the solar collector, which is derived from the hyperbolic distributed equation describing the heat transport dynamics by means of a dynamical Gaussian interpolation. Using the bilinear approximate model, a robust control strategy is designed applying Lyapunov stability theory combined with a phenomenological representation of the system in order to stabilize the tracking error. On the basis of the error analysis, simulation results show good performance of the proposed controller, in terms of tracking accuracy and convergence time, with limited measurement even under unfavorable working conditions. Furthermore, the presented work is of interest for a large category of dynamical systems knowing that the solar collector is representative of physical systems involving transport phenomena constrained by unknown external disturbances.

  6. Simultaneous tracking and activity recognition

    DEFF Research Database (Denmark)

    Manfredotti, Cristina Elena; Fleet, David J.; Hamilton, Howard J.

    2011-01-01

    Many tracking problems involve several distinct objects interacting with each other. We develop a framework that takes into account interactions between objects allowing the recognition of complex activities. In contrast to classic approaches that consider distinct phases of tracking and activity...

  7. Satellite and acoustic tracking device

    KAUST Repository

    Berumen, Michael L.

    2014-02-20

    The present invention relates a method and device for tracking movements of marine animals or objects in large bodies of water and across significant distances. The method and device can track an acoustic transmitter attached to an animal or object beneath the ocean surface by employing an unmanned surface vessel equipped with a hydrophone array and GPS receiver.

  8. Detecting multiple moving objects in crowded environments with coherent motion regions

    Science.gov (United States)

    Cheriyadat, Anil M.; Radke, Richard J.

    2013-06-11

    Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.

  9. Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes

    Directory of Open Access Journals (Sweden)

    Hengli Liu

    2015-01-01

    Full Text Available A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

  10. Symmetric Kullback-Leibler Metric Based Tracking Behaviors for Bioinspired Robotic Eyes.

    Science.gov (United States)

    Liu, Hengli; Luo, Jun; Wu, Peng; Xie, Shaorong; Li, Hengyu

    2015-01-01

    A symmetric Kullback-Leibler metric based tracking system, capable of tracking moving targets, is presented for a bionic spherical parallel mechanism to minimize a tracking error function to simulate smooth pursuit of human eyes. More specifically, we propose a real-time moving target tracking algorithm which utilizes spatial histograms taking into account symmetric Kullback-Leibler metric. In the proposed algorithm, the key spatial histograms are extracted and taken into particle filtering framework. Once the target is identified, an image-based control scheme is implemented to drive bionic spherical parallel mechanism such that the identified target is to be tracked at the center of the captured images. Meanwhile, the robot motion information is fed forward to develop an adaptive smooth tracking controller inspired by the Vestibuloocular Reflex mechanism. The proposed tracking system is designed to make the robot track dynamic objects when the robot travels through transmittable terrains, especially bumpy environment. To perform bumpy-resist capability under the condition of violent attitude variation when the robot works in the bumpy environment mentioned, experimental results demonstrate the effectiveness and robustness of our bioinspired tracking system using bionic spherical parallel mechanism inspired by head-eye coordination.

  11. Space Object Query Tool

    Science.gov (United States)

    Phillips, Veronica J.

    2017-01-01

    STI is for a fact sheet on the Space Object Query Tool being created by the MDC. When planning launches, NASA must first factor in the tens of thousands of objects already in orbit around the Earth. The number of human-made objects, including nonfunctional spacecraft, abandoned launch vehicle stages, mission-related debris and fragmentation debris orbiting Earth has grown steadily since Sputnik 1 was launched in 1957. Currently, the U.S. Department of Defenses Joint Space Operations Center, or JSpOC, tracks over 15,000 distinct objects and provides data for more than 40,000 objects via its Space-Track program, found at space-track.org.

  12. Objective Feature Identification and Tracking: A Review

    Science.gov (United States)

    1994-09-15

    these techniques in a visualization case study us- ferent approaches and modules can be put together ing the DieCAST model for the Gulf of Mexico... DieCAST model output for the Gulf equal magnitude but opposite sign. If the point of Mexico region. An example of the sharpness of being tested were to... DieCAST ocean Kittler, J. and J. Illingworth 1985: Relaxation circulation model in coastal and semi-enclosed labeling algorithms - a review.Image and

  13. Multi Object Tracking Using Parallel Processing

    DEFF Research Database (Denmark)

    Hussain, Dil muhammed Akbar

    2017-01-01

    such a system, however, when it comes to implementation of such complex system, computational power and memory are in the highest demand. Therefore, looking in totality one could use more than one processing unit to handle computation and memory demand. This presentation proposed a parallel processing...

  14. COCOA: tracking in aerial imagery

    Science.gov (United States)

    Ali, Saad; Shah, Mubarak

    2006-05-01

    Unmanned Aerial Vehicles (UAVs) are becoming a core intelligence asset for reconnaissance, surveillance and target tracking in urban and battlefield settings. In order to achieve the goal of automated tracking of objects in UAV videos we have developed a system called COCOA. It processes the video stream through number of stages. At first stage platform motion compensation is performed. Moving object detection is performed to detect the regions of interest from which object contours are extracted by performing a level set based segmentation. Finally blob based tracking is performed for each detected object. Global tracks are generated which are used for higher level processing. COCOA is customizable to different sensor resolutions and is capable of tracking targets as small as 100 pixels. It works seamlessly for both visible and thermal imaging modes. The system is implemented in Matlab and works in a batch mode.

  15. Robust automated knowledge capture.

    Energy Technology Data Exchange (ETDEWEB)

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

    2011-10-01

    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  16. Timber tracking

    DEFF Research Database (Denmark)

    Düdder, Boris; Ross, Omry

    2017-01-01

    Managing and verifying forest products in a value chain is often reliant on easily manipulated document or digital tracking methods - Chain of Custody Systems. We aim to create a new means of tracking timber by developing a tamper proof digital system based on Blockchain technology. Blockchain...

  17. Tracking Eyes using Shape and Appearance

    DEFF Research Database (Denmark)

    Hansen, Dan Witzner; Nielsen, Mads; Hansen, John Paulin

    2002-01-01

    We propose a non-intrusive eye tracking system intended for the use of everyday gaze typing using web cameras. We argue that high precision in gaze tracking is not needed for on-screen typing due to natural language redundancy. This facilitates the use of low-cost video components for advanced...... multi-modal interactions based on video tracking systems. Robust methods are needed to track the eyes using web cameras due to the poor image quality. A real-time tracking scheme using a mean-shift color tracker and an Active Appearance Model of the eye is proposed. From this model, it is possible...

  18. Dual Deep Network for Visual Tracking.

    Science.gov (United States)

    Chi, Zhizhen; Li, Hongyang; Lu, Huchuan; Yang, Minghsuan

    2017-02-15

    Visual tracking addresses the problem of identifying and localizing an unknown target in a video given the target specified by a bounding box in the first frame. In this paper, we propose a dual network to better utilize features among layers for visual tracking. It is observed that features in higher layers encode semantic context while its counterparts in lower layers are sensitive to discriminative appearance. Thus we exploit the hierarchical features in different layers of a deep model and design a dual structure to obtain better feature representation from various streams, which is rarely investigated in previous work. To highlight geometric contours of the target, we integrate the hierarchical feature maps with an edge detector as the coarse prior maps to further embed local details around the target. To leverage the robustness of our dual network, we train it with random patches measuring the similarities between the network activation and target appearance, which serves as a regularization to enforce the dual network to focus on target object. The proposed dual network is updated online in a unique manner based on the observation that the target being tracked in consecutive frames should share more similar feature representations than those in the surrounding background. It is also found that for a target object, the prior maps can help further enhance performance by passing message into the output maps of the dual network. Therefore, an independent component analysis with reference algorithm (ICA-R) is employed to extract target context using prior maps as guidance. Online tracking is conducted by maximizing the posterior estimate on the final maps with stochastic and periodic update. Quantitative and qualitative evaluations on two large-scale benchmark data sets show that the proposed algorithm performs favourably against the stateof- the-arts.

  19. A Bicriteria Approach for Robust Timetabling

    Science.gov (United States)

    Schöbel, Anita; Kratz, Albrecht

    Finding robust solutions of an optimization problem is an important issue in practice. Various concepts on how to define the robustness of an algorithm or of a solution have been suggested. However, there is always a trade-off between the best possible solution and a robust solution, called the price of robustness. In this paper, we analyze this trade-off using the following bicriteria approach. We treat an optimization problem as a bicriteria problem adding the robustness of its solution as an additional objective function. We demonstrate this approach at the aperiodic timetabling problem in which a timetable which is robust under delays is sought. We are able to derive necessary conditions for the resulting Pareto-optimal timetables. For the case in which the robustness is defined as the largest delay for which all connections are maintained we show the bicriteria problem can be solved with the same time complexity as the original single-criteria problem.

  20. How robust is a robust policy? A comparative analysis of alternative robustness metrics for supporting robust decision analysis.

    Science.gov (United States)

    Kwakkel, Jan; Haasnoot, Marjolijn

    2015-04-01

    In response to climate and socio-economic change, in various policy domains there is increasingly a call for robust plans or policies. That is, plans or policies that performs well in a very large range of plausible futures. In the literature, a wide range of alternative robustness metrics can be found. The relative merit of these alternative conceptualizations of robustness has, however, received less attention. Evidently, different robustness metrics can result in different plans or policies being adopted. This paper investigates the consequences of several robustness metrics on decision making, illustrated here by the design of a flood risk management plan. A fictitious case, inspired by a river reach in the Netherlands is used. The performance of this system in terms of casualties, damages, and costs for flood and damage mitigation actions is explored using a time horizon of 100 years, and accounting for uncertainties pertaining to climate change and land use change. A set of candidate policy options is specified up front. This set of options includes dike raising, dike strengthening, creating more space for the river, and flood proof building and evacuation options. The overarching aim is to design an effective flood risk mitigation strategy that is designed from the outset to be adapted over time in response to how the future actually unfolds. To this end, the plan will be based on the dynamic adaptive policy pathway approach (Haasnoot, Kwakkel et al. 2013) being used in the Dutch Delta Program. The policy problem is formulated as a multi-objective robust optimization problem (Kwakkel, Haasnoot et al. 2014). We solve the multi-objective robust optimization problem using several alternative robustness metrics, including both satisficing robustness metrics and regret based robustness metrics. Satisficing robustness metrics focus on the performance of candidate plans across a large ensemble of plausible futures. Regret based robustness metrics compare the