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Combinatorial Fusion Criteria for Real-Time Tracking

Combinatorial Fusion Criteria for Real-Time Tracking

引用

International Conference on Advanced Information Networking and Applications (AINA)

作者： D.F. Hsu D.M. Lyons J. Ai Computer Vision & Robotics Laboratory Department of Computer & Information Science Fordham University Bronx NY USA

We address the problem of automated video tracking of targets when targets undergo multiple mutual occlusions. Our approach is based on the idea that as targets are occluded, selection of feature subsets and combinations of those features are effective in identifying the target and improving tracking performance. We use combinatorial fusion analysis to develop a metric to select which subset of features will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results to illustrate the performance of the proposed metric

关键词： Target tracking Target recognition computer vision robotics and automation Diversity reception Robot vision systems Laboratories Information science Surveillance Robot sensing systems

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Stereo Matching with Symmetric Cost Functions

Stereo Matching with Symmetric Cost Functions

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Kuk-Jin Yoon In So Kweon Robotics and Computer Vision Laboratory Department Electrical Engineering and Computer Science KAIST Daejeon South Korea

Recently, many global stereo methods have achieved good results by modeling a disparity surface as a Markov random field (MRF) and by solving an optimization problem with various techniques. However, most global methods mainly focus on how to minimize conventional cost functions efficiently, although it is more important to define cost functions well to improve performance. In this paper, we propose new symmetric cost functions for global stereo methods. We first present a symmetric data cost function for the likelihood and then propose a symmetric discontinuity cost function for the prior in the MRF model for stereo. In defining cost function, both the reference image and the target image are taken into account to improve performance without modeling half-occluded pixels explicitly and without using color segmentation. The performance improvement of stereo matching due to the proposed symmetric cost functions is verified by applying the proposed symmetric cost functions to the belief propagation (BP) based stereo method. Experimental results for standard testbed images show that the performance of the BP based stereo method is greatly improved by the proposed symmetric cost functions.

关键词： Cost function Stereo vision Pixel computer vision Markov random fields Optimization methods Image segmentation Belief propagation Robot vision systems computer science

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Improving the efficiency and effectiveness of railcar safety appliance inspection using machine vision technology

Improving the efficiency and effectiveness of railcar safety...

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ASME/IEEE Joint Conference on Rail

作者： R. Edwards C.P.L. Barkan J.M. Hart S. Todorovic N. Ahuja Department of Civil and Environmental Engineering Newmark Civil Engineering Laboratory University of Illinois Urbana-Champaign Urbana IL USA Computer Vision and Robotics Laboratory Beckman Institute for Advanced Science and Technology Urbana IL USA Department of Electrical and Computer Engineering Computer Vision and Robotics Laboratory Beckman Institute for Advanced Science and Technology Urbana IL USA

Before a train departs a yard, many aspects of the freight cars and locomotives undergo inspection, including their safety appliances. Safety appliances are handholds, ladders and other objects that serve as the interface between humans and railcars during transportation. Federal safety rules govern the design and condition of safety appliances. The current car inspection process is primarily visual making it laborious, redundant, and generally lacking of memory. There exists a potential to increase both the effectiveness and efficiency of safety appliance inspections by utilizing machine vision technology to enhance the railcar inspection process. Machine vision consists of capturing digital video and using algorithms capable of detecting and analyzing the particular objects or patterns of interest. computer algorithms can objectively inspect railcars without tiring or becoming distracted and can also focus on certain parts of the railcar not easily seen by an inspector on the ground. Thus far, algorithms have been developed that can detect deformed ladders, handholds, and brake wheels on open-top gondolas and hoppers. Next, visual learning will be employed to teach the algorithm the differences between Federal Railroad Administration (FRA) safety appliance defects and other types of deformation not requiring a car to be bad ordered. The final product will be a wayside inspection system capable of detecting safety appliance defects on passing railcars.

关键词： Railway safety Home appliances Inspection Machine vision Vehicle safety US Department of Transportation Humans Rail transportation Object detection Pattern analysis

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A visual servoing approach for tracking features in urban areas using an autonomous helicopter

A visual servoing approach for tracking features in urban ar...

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IEEE International Conference on robotics and Automation (ICRA)

作者： L. Mejias P. Campoy S. Saripalli G.S. Sukhatme Computer Vision Group Universidad Politécnica de Madrid Madrid Spain Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California Los Angeles CA USA

The use of unmanned aerial vehicles (UAVs) in civilian and domestic applications is highly demanding, requiring a high-level of capability from the vehicles. This work addresses the design and implementation of a vision-based feature tracker for an autonomous helicopter. Using vision in the control loop allows estimating the position and velocity of a set of features with respect to the helicopter. The helicopter is then autonomously guided to track these features (in this case windows in an urban environment) in real time. The results obtained from flight trials in a real world scenario demonstrate that the algorithm for tracking features in an urban environment, used for visual servoing of an autonomous helicopter is reliable and robust

关键词： Visual servoing Urban areas Helicopters Aircraft navigation Machine vision Control systems Unmanned aerial vehicles Global Positioning System computer vision Robot vision systems

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Rotational legged locomotion

Rotational legged locomotion

引用

12th International Conference on Advanced robotics, 2005. ICAR '05

作者： Lyons, Damian M. Pamnany, Kiran Robotics and Computer Vision Laboratory Department of Computer and Information Science Fordham University Bronx NY 10458

ISBN: (纸本)0780391772

In this paper we presented a novel, agile robot mechanism, which we call a rotopod, which combines aspects of wheeled and legged locomotion. A general description of how a tripedal rotopod can be made to step, rotating the mechanism about one leg, and moving the center of the mechanism, is presented. The concept of a gait for this mechanism is defined, and is used to show how extremely agile the mechanism can be. Specific resistance is employed as a way to explore the relative efficiency of this mechanism versus a wheel. Finally, we describe our first prototype rotopod and report on experiments conducted to characterize stepping. © 2005 IEEE.

关键词： Gait analysis

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Rank-based multisensory fusion in multitarget video tracking

Rank-based multisensory fusion in multitarget video tracking

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IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2005

作者： Lyons, Damian M. Hsu, D. Frank Robotics and Computer Vision Laboratory Department of Computer and Information Science Fordham University Bronx NY 10458

ISBN: (纸本)0780393856

An attractive approach to improve tracking performance for visual surveillance is to use information from multiple visual sensory cues such as position, color, shape, etc. Previous work in fusion for tracking has tended to focus on fusion by numerically combining the scores assigned by each cue. We argue that for video scenes with many targets in a crowded situation, the splitting and merging of regions associated with targets, and the subsequent dramatic changes in cue values and reliabilities, renders this form of fusion less effective. In this paper we present experimental results showing that use of cue rank information in fusion produces a significantly better tracking result in crowded scenes. We also present a formalization of this fusion problem as a step in understanding why this effect occurs and how to build a tracking system that exploits it. © 2005 IEEE.

关键词： Tracking (position)

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A dynamic pruning and feature selection strategy for real-time tracking

A dynamic pruning and feature selection strategy for real-ti...

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19th International Conference on Advanced Information Networking and Applications, AINA 2005

作者： Hsu, D. Frank Lyons, Damian M. Computer Vision and Robotics Laboratory Department of Computer and Information Science Fordham University Bronx NY 10458 United States

ISBN: (纸本)0769522491

Automated video tracking is useful in a number of applications such as surveillance, multisensor networks, robotics and virtual reality. In this paper we investigate an approach to tracking based on fusing the output of a collection of video trackers, each attending to a different feature or cue on the target. We show both theoretically and experimentally that the method used to prune the growth of target hypotheses can have a great impact on the trackers performance, and indirectly, change the benefit of using linear score combination as opposed to a non-linear rank combination for fusion. We also show that the rank-score graph defined by Hsu and Taksa can be used to select a subset of features to fuse to reduce classification error. © 2005 IEEE.

关键词： Real time systems

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Locally adaptive support-weight approach for visual correspondence search

Locally adaptive support-weight approach for visual correspo...

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2005 IEEE computer Society Conference on computer vision and Pattern Recognition, CVPR 2005

作者： Yoon, Kuk-Jin Kweon, In-So Robotics and Computer Vision Laboratory Dept. of Electrical Engineering and Computer Science KAIST 373-1 Guseong-dong Yuseong-gu Daejeon 305-701 Korea Republic of

ISBN: (纸本)0769523722

In this paper, we present a new area-based method for visual correspondence search that focuses on the dissimilarity computation. Local and area-based matching methods generally measure the similarity (or dissimilarity) between the image pixels using local support windows. In this approach, an appropriate support window should be selected adaptively for each pixel to make the measure reliable and certain. Finding the optimal support window with an arbitrary shape and size is, however, very difficult and generally known as an NP-hard problem. For this reason,unlike the existing methods that try to find an optimal support window, we adjusted the support-weight of each pixel in a given support window. The adaptive support-weight of a pixel is computed based on the photometric and geometric relationship with the pixel under consideration. Dissimilarity is then computed using the raw matching costs and support-weights of both support windows, and the correspondence is finally selected by the WTA (Winner-Takes-All) method. The experimental results for the rectified real images show that the proposed method successfully produces piecewise smooth disparity maps while preserving sharp depth discontinuities accurately.

关键词： Visual communication

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Locally adaptive support-weight approach for visual correspondence search

Locally adaptive support-weight approach for visual correspo...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Kuk-Jin Yoon In-So Kweon Robotics and Computer Vision Laboratory Department of Electrical Engineering and Computer Science KAIST Daejeon South Korea

ISBN: (纸本)0769523722

In this paper, we present a new area-based method for visual correspondence search that focuses on the dissimilarity computation. Local and area-based matching methods generally measure the similarity (or dissimilarity) between the image pixels using local support windows. In this approach, an appropriate support window should be selected adaptively for each pixel to make the measure reliable and certain. Finding the optimal support window with an arbitrary shape and size is, however, very difficult and generally known as an NP-hard problem. For this reason, unlike the existing methods that try to find an optimal support window, we adjusted the support-weight of each pixel in a given support window. The adaptive support-weight of a pixel is computed based on the photometric and geometric relationship with the pixel under consideration. Dissimilarity is then computed using the raw matching costs and support-weights of both support windows, and the correspondence is finally selected by the WTA (winner-takes-all) method. The experimental results for the rectified real images show that the proposed method successfully produces piecewise smooth disparity maps while preserving sharp depth discontinuities accurately.

关键词： Shape Pixel Costs computer vision NP-hard problem Robot vision systems Laboratories computer science Area measurement Photometry

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A dynamic pruning and feature selection strategy for real-time tracking

A dynamic pruning and feature selection strategy for real-ti...

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International Conference on Advanced Information Networking and Applications (AINA)

作者： D.F. Hsu D.M. Lyons Computer Vision & Robotics Laboratory Department of Computer & Information Science Fordham University Bronx NY USA

关键词： Target tracking robotics and automation Fuses computer vision Surveillance Virtual reality Time measurement Robot vision systems Laboratories Information science

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