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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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Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Large-Area Photo-Mosaics Using Global Alignment and Navigati...

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OCEANS

作者： J. Ferrer A. Elibol O. Delaunoy N. Gracias R. Garcia Computer Vision and Robotics Group UNiversity of Girona Spain Computer Vision and Robotics Group University of Girona Spain

ISBN: (纸本)9780933957374

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported.

关键词： Navigation Oceans USA Councils Real time systems

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REAL-TIME vision BASED AUV NAVIGATION SYSTEM USING A COMPLEMENTARY SENSOR SUITE

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IFAC Proceedings Volumes 2007年第17期40卷 373-378页

作者： Jonathan Horgan Daniel Toal Pere Ridao Rafael Garcia 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

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.

关键词： marine robotics robot vision Kalman filtering robot navigation

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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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Head Pose Estimation for Driver Assistance Systems: A Robust Algorithm and Experimental Evaluation

Head Pose Estimation for Driver Assistance Systems: A Robust...

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International Conference on Intelligent Transportation

作者： Erik Murphy-Chutorian Anup Doshi Mohan Manubhai Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

Recognizing driver awareness is an important prerequisite for the design of advanced automotive safety systems. Since visual attention is constrained to a driver's field of view, knowing where a driver is looking provides useful cues about his activity and awareness of the environment. This work presents an identity-and lighting-invariant system to estimate a driver's head pose. The system is fully autonomous and operates online in daytime and nighttime driving conditions, using a monocular video camera sensitive to visible and near-infrared light. We investigate the limitations of alternative systems when operated in a moving vehicle and compare our approach, which integrates Localized Gradient Orientation histograms with support vector machines for regression. We estimate the orientation of the driver's head in two degrees-of-freedom and evaluate the accuracy of our method in a vehicular testbed equipped with a cinematic motion capture system.

关键词： Robustness Magnetic heads Automotive engineering Safety Cameras Remotely operated vehicles Histograms Support vector machines Motion estimation System testing

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Video Based Surround Vehicle Detection, Classification and Logging from Moving Platforms: Issues and Approaches

Video Based Surround Vehicle Detection, Classification and L...

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IEEE Symposium on Intelligent Vehicle

作者： Tarak Gandhi Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

This paper discusses the issues and approaches involved in developing a mobile vehicle-mounted system to detect, classify, and log the surrounding vehicles in a database for efficient query-based retrieval. This system consists of three components: (1) vehicle sensing, detection, and tracking (2) feature extraction and classification (3) database storage and retrieval. Relevant research in each of these components is described in order to guide the development of such a system. Such a system has applications including traffic analysis from mobile probes, analyzing driver behavior based on surrounding vehicles, as well as surveillance from mobile platform.

关键词： Vehicle detection Cameras Road vehicles Information retrieval Image sensors Vehicle driving Object detection Monitoring Layout Laser radar

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Combinatorial Fusion Criteria for Robot Mapping

Combinatorial Fusion Criteria for Robot Mapping

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Damian M. Lyons D. Frank Hsu Qiang Ma Liang Wang Computer Vision & Robotics Laboratory Department of Computer & Information Science Fordham University Bronx NY USA

We address the problem of sensor fusion for stereo and ultrasound depth measurements for map building for a robot operating in a cluttered environment. In such a situation it's difficult to make useful and realistic assumptions about the sensor or environment statistics. Combinatorial Fusion Analysis is used to develop an approach to fusion with unknown sensor and environment statistics. A metric is proposed that shows when fusion from a set of fusion alternatives will produce a more accurate estimation of depth than either sonar or stereo alone and when not. The metric consists of two criteria: (a) the performance ratio PR(A,B) between sensors A and B, and (b) the diversity d(A,B) between A and B as captured by the rank-score function fA and fB. Experimental results are reported to illustrate that these two CFA criteria are viable predictors to distinguish between positive cases (the combined system performs better than or equal to the individual systems) and negative cases.

关键词： Sensor fusion Robot sensing systems Robot vision systems Statistics computer vision Stereo vision Sonar Mobile robots Ultrasonic imaging Statistical analysis

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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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Workshop on Motion and Video Computing

作者： Sangho Park Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego CA USA

ISBN: (纸本)9781424431366;9780769527932

关键词： Humans Cameras computer vision Condition monitoring Robot vision systems Machine vision Feedback Motion analysis computerized monitoring Image analysis

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