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International Conference on Pattern Recognition

作者： Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California La Jolla CA USA

ISBN: (纸本)9781424421749

This paper presents an adaptive framework for live video analysis. The activities of surveillance subjects are described using a spatio-temporal vocabulary learned from recurrent motion patterns. The repetitive nature of object trajectories are used to build a topographical map, where nodes are points of interest and the edges correspond to activities, to describe a scene. The graph is learned in an unsupervised manner but is flexible and able to adjust to changes in the environment or other scene variations.

关键词： Layout Surveillance Hidden Markov models Video compression Vocabulary Cameras computer vision Robot vision systems Laboratories Trajectory

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Hand modeling and tracking from voxel data: An integrated framework with automatic initialization

Hand modeling and tracking from voxel data: An integrated fr...

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International Conference on Pattern Recognition

作者： Cuong Tran Mohan M. Trivedi Computer Vision and Robotics Research Laboratory (CVRR) University of California San Diego CA USA

ISBN: (纸本)9781424421749

We propose an integrated framework for automated hand model initialization and tracking using voxel data. Starting with an initial specific hand pose, the Laplacian Eigenspace (LE) based segmentation method is applied to segment hand voxel into different parts. This segmentation result is then used to extend the kinematically constrained gaussian mixture model (KC-GMM) method for articulated body pose inference with an automated hand model initialization. Our experiment with both synthesized hand voxel and real hand voxel captured from multi-perspective thermal cameras show that by combining the two methods, we have a more powerful system than using each one solitarily.

关键词： Power system modeling Cameras Torso Human computer interaction Image reconstruction Kinematics computer vision Robot vision systems robotics and automation Laboratories

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3D tracking and dynamic analysis of human head movements and attentional targets

3D tracking and dynamic analysis of human head movements and...

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Erik Murphy-Chutorian Mohan M. Trivedi Systems for Human Interactivity Visualization and Analysis Computer Vision and Robotics Research Laboratory University of California San Diego USA

We present a new system-level framework for the automatic detection and tracking of multiple persons' heads in intelligent meeting rooms. We implement this approach with a distributed array of cameras that detect the meeting participants and continuously estimate their head orientation and head movements in 6 degrees-of-freedom with fine precision. The initial position of each person is obtained with a set of face detectors coupled with a new iterative approach to resolve the 3D ambiguities from overlapping epipolar lines. The head pose is obtained from a hybrid head pose estimation and tracking scheme that combines support vector regressors with a new multi-view 3D model-based tracking system. The purpose of this system is to facilitate the automatic semantic analysis of group meetings. As an example application, we evaluate the ability of the system to estimate the person that receives the most visual attention in the form of head direction.

关键词： Head Magnetic heads Cameras Three dimensional displays Face Estimation Visualization

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Mobile robot localization using panoramic vision and combinations of feature region detectors

Mobile robot localization using panoramic vision and combina...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Arnau Ramisa Adriana Tapus Ramon Lopez de Mantaras Ricardo Toledo Artificial Intelligence Research Institute Spain Robotics Research Lab Interaction Lab Department of Computer Science University of Southern California Los Angeles USA UAB Campus Computer Vision Center Spain

This paper presents a vision-based approach for mobile robot localization. The environmental model is topological. The new approach uses a constellation of different types of affine covariant regions to characterize a place. This type of representation permits a reliable and distinctive environment modeling. The performance of the proposed approach is evaluated using a database of panoramic images from different rooms. Additionally, we compare different combinations of complementary feature region detectors to find the one that achieves the best results. Our experimental results show promising results for this new localization method. Additionally, similarly to what happens with single detectors, different combinations exhibit different strengths and weaknesses depending on the situation, suggesting that a context-aware method to combine the different detectors would improve the localization results.

关键词： Mobile robots computer vision Detectors Robot kinematics Robot localization Feature extraction Fingerprint recognition robotics and automation USA Councils Image databases

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Real-time vision based auv navigation system using a complementary sensor suite

Real-time vision based auv navigation system using a complem...

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作者： Horgan, Jonathan Toal, Daniel Ridao, Pere Garcia, Rafael Mobile and Marine Robotics Research Centre Department of Electronic and Computer Engineering University of Limerick Ireland Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Spain

ISBN: (纸本)9783902661623

This paper proposes a real-time navigation system for an AUV that takes advantage of the complementary performance of a sensor suite including a DVL, a compass, a depth sensor and altimeter sensors with a feature based motion estimator using vision. To allow for real-time performance of the vision based motion estimator a simple but fast correlation algorithm is used for feature matching. The compass and the depth sensors are used to bound the drift of the heading and depth estimations respectively. The altimeter is required in order to translate the feature displacements measured from the images into the metric displacements of the robot. While the robot must rely on DVL navigation above a certain altitude where vision is useless, DVL measurements can be complemented with higher frequency accurate motion estimates from the vision system when navigating close to the seafloor. Copyright © 2007 IFAC.

关键词： Navigation systems

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A two-stage multi-view analysis framework for human activity and interactions

A two-stage multi-view analysis framework for human activity...

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2007 IEEE Workshop on Motion and Video Computing, WMVC 2007

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego San Diego CA 92037

ISBN: (纸本)0769527930

This paper presents a new framework for a multi-stage multi-view approach for human interactions and activity analysis. The analysis is performed in a distributed vision system that synergistically integrate track- and body-level representations across multiple cameras. Our system aims at versatile and easily-deployable system that does not require careful camera calibration. Main contributions of the paper are: (1) context-dependent camera handover for occlusion handling, (2) switching the multi-stage analysis between track- and body-level representations, and (3) a hypothesis-verification paradigm for top-down feedback exploiting spatio-temporal constraints inherent in human interaction. Experimental evaluation shows the efficacy of the proposed system for analyzing multi-person interactions. Current implementation uses two views, but extension to more views is straightforward. © 2007 IEEE.

关键词： Human computer interaction

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Homography-based analysis of people and vehicle activities in crowded scenes

Homography-based analysis of people and vehicle activities i...

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7th IEEE Workshop on Applications of computer vision, WACV 2007

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego San Diego CA 92037

ISBN: (纸本)0769527949

This paper presents an new framework for homographybased analysis of pedestrian-vehicle activity in crowded scenes. Planar homography constraint is exploited to extract view-invariant object features including footage area and velocity of objects on the ground plane. Spatiotemporal relationships between people- and vehicle- tracks are represented by a semantic event. Context awareness of the situation is achieved by the estimated density distribution of objects and the anticipation of possible directions of near-future tracks using piecewise velocity history. Singleview and multi-view based homography mapping options are compared. Our framework can be used to enhance situational awareness for disaster prevention, human interactions in structured environments, and crowd movement analysis at wide regions. © 2007 IEEE.

关键词： Feature extraction

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Satellite imagery based adaptive background models and shadow suppression

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Signal, Image and Video Processing 2007年第2期1卷 119-132页

作者： Doshi, Anup Trivedi, Mohan Manubhai Computer Vision and Robotics Research Laboratory University of California at San Diego San Diego CA 92093-0434 9500 Gilman Drive United States

Accurate segmentation of foreground objects in video scenes is critical for assuring reliable performance of vision systems for object tracking and situational awareness in outdoor scenes. Most existing techniques for background modeling and shadow suppression require that a number of parameters be "hand-tuned" based on environmental conditions. This paper presents two contributions to overcome such limitations. First, we develop and demonstrate a satellite imagery based approach for selecting appropriate background and shadow models. It is shown that the illumination conditions (i.e. cloud cover) of a scene can be reliably inferred from visible satellite images in the local region of the camera. The second contribution presented in the paper is introduction and evaluation of a Hybrid Cone-Cylinder Codebook (HC3) model which combines an adaptive efficient background model with HSV-color space shadow suppression into a single coherent framework. The structure of the HC3 model allows for seamless fusion of the satellite data. We are thereby able to exploit the fact that, for example, shadows are more pronounced on sunny days than cloudy days, allowing for more sensitive detection. The paper presents a set of experiments using day long sequences of videos from an operational surveillance system testbed. Results of these experimental analyses quantitatively illustrate the benefits of using satellite imagery to inform and adaptively adjust background and shadow modeling. © Springer-Verlag London Limited 2007.

关键词： Cloud radiance Foreground-background segmentation Hybrid Cone-Cylinder Codebook (HC3) Shadow suppression Satellite imagery

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Representing shape with a spatial pyramid kernel 07

Representing shape with a spatial pyramid kernel

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6th ACM International Conference on Image and Video Retrieval, CIVR 2007

作者： Bosch, Anna Zisserman, Andrew Munoz, Xavier University of Girona Computer Vision Group 17003 Girona Spain University of Oxford Robotics Research Group OX1 3PJ Oxford United Kingdom

ISBN: (纸本)1595937331

The objective of this paper is classifying images by the object categories they contain, for example motorbikes or dolphins. There are three areas of novelty. First, we introduce a descriptor that represents local image shape and its spatial layout, together with a spatial pyramid kernel. These are designed so that the shape correspondence between two images can be measured by the distance between their descriptors using the kernel. Second, we generalize the spatial pyramid kernel, and learn its level weighting parameters (on a validation set). This significantly improves classification performance. Third, we show that shape and appearance kernels may be combined (again by learning parameters on a validation set). Results are reported for classification on Caltech-101 and retrieval on the TRECVID 2006 data sets. For Caltech-101 it is shown that the class specific optimization that we introduce exceeds the state of the art performance by more than 10%. Copyright 2007 ACM.

关键词： Shape optimization

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