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ACM SIGGRAPH 2007 Sketches, SIGGRAPH'07

作者： Jobin, Jean-Philippe Comtois, Sylvain Gosselin, Clément Faguy, Robert Laurendeau, Denis Robotics Laboratory Computer Vision and Systems Lab. LANTISS Laval University Quebec City Canada

The hero jumped down the wall, escalated the hill, slid down the rock, climbed the stairs and finally left the vilain behind...In this classical scene, the hero has to move on different types of terrain. Recreating su...

ISBN: (纸本)9781450347266

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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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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

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.

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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Homography-based Analysis of People and Vehicle Activities in Crowded Scenes

Homography-based Analysis of People and Vehicle Activities i...

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IEEE Workshop on Applications of computer vision (WACV)

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

This paper presents an new framework for homography-based 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. Spatio-temporal 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. Single-view 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

关键词： Vehicles Layout Surveillance Humans computer vision Cameras Robot vision systems Safety Transmission line matrix methods Feature extraction

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An application framework for measuring the performance of a visual servo control of a reaching task for the visually impaired

An application framework for measuring the performance of a ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Duane J. Jacques Ranga Rodrigo Kenneth A. McIsaac Jagath Samarabandu Computer Vision and Mobile Robotics Laboratory at the Department of Electrical and Computer Engineering University of Western Ontario London ONT Canada

In this work, we propose a framework that can provide performance metrics with regards to the usability of an assistive device designed to provide visual servoing of a reaching task performed by a visually impaired individual. The framework provides a model and methodology from which performance metrics can be synthesized based on robotic manipular kinematics and an adaptation of Fitts' law for reaching task motions in a 3D environment. The purpose of which is to facilitate an understanding of how well the system's design accommodates the user's natural movement style when performing the reaching task. Use of advances in visual tracking techniques employing scale, view-point, and illumination invariant features are incorporated to allow for a further decoupling of the feature space from the joint-level control space.

关键词： Servosystems Visual servoing Prototypes Mobile robots Robot sensing systems Humans Measurement Target tracking Cameras Object detection

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A Cable-driven Parallel Mechanism for Capturing Object Appearance from Multiple Viewpoints

A Cable-driven Parallel Mechanism for Capturing Object Appea...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： J.-D. Deschenes P. Lambert S. Perreault N. Martel-Brisson N. Zoso A. Zaccarin P. Hebert S. Bouchard C. M. Gosselin Computer Vision and Systems Laboratory Laval University Canada Robotics Laboratory at the Department of Mechanical Engineering Laval University Canada

This paper presents the full proof of concept of a system for capturing the light field of an object. It is based on a single high resolution camera that is moved all around the object on a cable-driven end-effector. The main advantages of this system are its scalability and low interference with scene lighting. The camera is accurately positioned along hemispheric trajectories by observing target features. From the set of gathered images, the visual hull is extracted and can be used as an approximate geometry for mapping a surface light field. The paper describes the acquisition system as well as the modeling process. The ability of the system to produce models is validated with four different objects whose sizes range from 20 cm to 3 m.

关键词： Cameras Robot vision systems Cable TV Laboratories Trajectory Geometry Cables computer vision Mechanical engineering Scalability

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On the Spacetime Geometry of Galilean Cameras

On the Spacetime Geometry of Galilean Cameras

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Yaser Sheikh Alexei Gritai Mubarak Shah Robotics Institute Carnegie Mellon University USA Computer Vision Laboratory University of Central Florida USA

In this paper, a projection model is presented for cameras moving at constant velocity (which we refer to as Galilean cameras). To that end, we introduce the concept of spacetime projection and show that perspective imaging and linear pushbroom imaging are specializations of the proposed model. The epipolar geometry between two such cameras is developed and we derive the Galilean fundamental matrix. We show how six different "fundamental" matrices can be directly recovered from the Galilean fundamental matrix including the classic fundamental matrix, the linear pushbroom (LP) fundamental matrix and a fundamental matrix relating epipolar plane images (EPIs). To estimate the parameters of this fundamental matrix and the mapping between videos in the case of planar scenes we describe linear algorithms and report experimental performance of these algorithms.

关键词： Cameras Transmission line matrix methods Videos Robot vision systems Layout computer vision Laboratories Parameter estimation Computational geometry Orbital robotics

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