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Conference on computer vision and Pattern Recognition (CVPR)

作者： I. Mikic M. Trivedi E. Hunter P. Cosman Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California La Jolla CA USA

ISBN: (纸本)0769512720

We present a framework for articulated body model acquisition and tracking from voxel data. A 3D voxel reconstruction of the person's body is computed from silhouettes extracted from four cameras. The model acquisition process is fully automated. In the first frame, body parts are located sequentially. The head is located first, since its shape and size are unique and stable. Other parts are found by sequential template growing and fitting. This initial estimate of body part locations, sizes and orientations is then used as a measurement for the extended Kalman filter which ensures a valid articulated body model. The same filter, with a slightly modified state and state transition matrix, is then used for tracking. The performance of the system has been evaluated on several video sequences with promising results.

关键词： Cameras Image reconstruction Biological system modeling Data mining computer vision Robot vision systems Head Shape Filters Image segmentation

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Visual Modules for Head Gesture Analysis in Intelligent Vehicle Systems

Visual Modules for Head Gesture Analysis in Intelligent Vehi...

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IEEE Symposium on Intelligent Vehicle

作者： Junwen Wu M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California San Diego CA USA

In this paper a coarse-to-fine system framework for analyzing the head gesture is presented. We discuss several important modules from computer vision aspects, including the pose-invariant face detection, face tracking, pose determination and high-resolution image reconstruction for eye pupils detection. Visual cues using intensity images obtained from in-car cameras are explored. A pose-invariant face detection algorithm is used to get the initial face area; afterwards face tracking and validation step is proposed to segment the face region for pose determination. The algorithm is tested on the drivers images under natural driving conditions. Experimental results show that the algorithm is robust to the head pose changes as well as the illumination changes. In this system framework, we propose that when coarse analysis utilizing the head pose alone is not sufficient for driver's behavior analysis, a finer analysis based on the eye gaze tracking is used, which requires images with sufficient resolution. A novel super-resolution reconstruction algorithm is proposed to help reveal more facial details, so as to facilitate the pupil detection. Experiment on the synthesis data shows the effectiveness of the super-resolution reconstruction algorithm

关键词： Intelligent vehicles Face detection Head Image analysis Reconstruction algorithms computer vision Image reconstruction Cameras Image segmentation Testing

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A Regression Model in TensorPCA Subspace for Face Image Super-resolution Reconstruction

A Regression Model in TensorPCA Subspace for Face Image Supe...

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International Conference on Pattern Recognition

作者： Junwen Wu M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California San Diego CA USA

ISBN: (纸本)0769525210

A regression model in the tensorPCA subspace is proposed in this paper for face super-resolution reconstruction. An approximate conditional probability model is used for the tensor subspace coefficients and maximum-likelihood estimator gives a linear regression model. The approximation is corrected by adding non-linear component from a RBF-type regressor. Experiments on face images from FERET database validate the algorithm. Although each projection coefficient is estimated by a local estimator, tensorPCA subspace analysis is still a global descriptor, which makes the algorithm have certain ability to deal with partially occluded images

关键词： Image resolution Image reconstruction Tensile stress Spatial resolution Principal component analysis Face detection Image analysis computer vision Robot vision systems Laboratories

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EARLY ORIENTATION SELECTION—INFERRING TRACE, TANGENT, AND CURVATURE FIELDS

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International Journal of Pattern Recognition and Artificial Intelligence 1988年第3期2卷 443-457页

作者： STEVEN W. ZUCKER Canadian Institute for Advanced Research Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montréal Québec Canada

Orientation selection is the inference of orientation information out of images. It is one of the foundations on which other visual structures are built, since it must precede the formation of contours out of pointillist data and surfaces out of surface markings. We take a differential geometric view in defining orientation selection and develop algorithms for actually doing it. The goal of these algorithms is formulated in mathematical terms as the inference of a vector field of tangents (to the contours), and the algorithms are studied in both abstract and computational forms. They are formulated as matching problems, and algorithms for solving them are reduced to biologically plausible terms. We show that two different matching problems are necessary, the first for 1-dimensional contours (which we refer to as Type I processes) and the second for 2-dimensional flows (or Type II processes).

关键词： computer vision Orientation selection Curve detection Relaxation Edge detection Texture

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The mapping of texture on VR polygonal models 2

The mapping of texture on VR polygonal models

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2nd International Conference on 3-D Digital Imaging and Modeling, 3DIM 1999

作者： Laurendeau, Denis Bertrand, Nathalie Houde, Régis Computer Vision and Systems Laboratory Department of Electrical Engineering and Computer Engineering Laval University QuebecQCG1K 7P4 Canada Robotics Division Hydro Quebec Research Institute VarennesQCJ3X 1S1 Canada

ISBN: (纸本)0769500625

The paper addresses the problem of choosing automatically, and without user intervention, the best possible 2D image that should be used to map as a texture on polygons of a geometric model of complex scenes made of several objects. The geometric models and the texture data are obtained separately: the models are built from range data while the texture information is obtained from 2D color images of the scene. The system does not make any assumption on the way the texture data has been acquired. Texture selection results are presented for an indoor scene. © 1999 IEEE.

关键词： Image texture

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New generation of multirobot systems

New generation of multirobot systems

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IEEE International Conference on Systems, Man and Cybernetics

作者： M.M. Trivedi K.C. Ng N. Lassiter R. Capella Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of California San Diego La Jolla CA USA

This paper presents a summary of a comprehensive research project involving development of a completely autonomous multirobot system for railway track maintenance applications. The specifications of this "real-world" application required us to consider a multirobot system conceptualization, rather than a single robot system.

关键词： Multirobot systems Rail transportation Robot sensing systems robotics and automation Sensor arrays Fasteners computer vision Application software Sensor systems Intelligent robots

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Designing stereo heads using task domain constraints

Designing stereo heads using task domain constraints

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International Conference on Pattern Recognition

作者： S.M. Thayer C.S. Gourley Electrical and Compute Engineering Department Computer Vision and Robotics Research Laboratory University of Tennessee Knoxville TN USA

A novel paradigm for the synthesis of convergent-axis stereo geometries is presented. This paradigm incorporates constraints that represent task-oriented properties that can be easily derived in many applications of stereo-ranging, particularly those involving manipulation. Given these properties, a solution that selects the set of optimal design parameters, in the sense of accuracy, under the given constraints is presented. Results of this algorithm are discussed and analyzed in terms of the optimality of the minimum-area technique used in the derivation.

关键词： Cameras Stereo vision Solid modeling computer vision Laboratories Lenses Equations Robot vision systems Computational geometry Contracts

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Multiperspective Thermal IR and Video Arrays for 3D Body Tracking and Driver Activity Analysis

Multiperspective Thermal IR and Video Arrays for 3D Body Tra...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Shinko Y. Cheng Sangho Park M.M. Trivedi Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA

This paper presents a multi-perspective (i.e., four camera views) multi-modal (i.e., thermal infrared and color) video based system for robust and real-time 3D tracking of important body *** multi-perspective characteristics of the system provides 3Dtrajectory of the body parts, while the multi-modal characteristics of the system provides robustness and reliability of feature detection and tracking. The application context for this research is that of intelligent vehicles and driver assistance systems. Experimental results demonstrate effectiveness of the proposed system.

关键词： Cameras computer vision Infrared detectors Humans Head Robustness Robot vision systems Image color analysis Real time systems Intelligent vehicles

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Real-time stereo-based vehicle occupant posture determination for intelligent airbag deployment

Real-time stereo-based vehicle occupant posture determinatio...

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IEEE Symposium on Intelligent Vehicle

作者： T.D. Schoenmackers M.M. Trivedi Department of Electrical and Computer Engineering Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

From 1990 to April 2002, according to the National Highway Traffic Safety Administration (NHTSA), airbag deployment has been responsible for 208 deaths in low-severity crashes. Of these deaths, 107 were children between the ages of 1 and 11, 22 were infants, and 32 were women under the height of five feet two inches. In addition to deaths, airbags are responsible for many more incidental injuries and broken bones. These injuries could be avoided if the system had an accurate model of the actual pose of the occupant. This paper discusses a system we are developing to accurately determine the position of the head, torso, and arms of the front-seat occupant of a vehicle.

关键词： Intelligent vehicles Head Intelligent robots US department of Transportation Pediatrics Injuries Torso Intelligent sensors Road vehicles Vehicle safety

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Driver's view and vehicle surround estimation using omnidirectional video stream

Driver's view and vehicle surround estimation using omnidire...

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IEEE Symposium on Intelligent Vehicle

作者： K.S. Huang M.M. Trivedi T. Gandhi Computer Vision and Robotics Research (CVRR) Laboratory Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA

Our research is focused on the development of novel machine vision based telematic systems, which provide non-intrusive probing of the state of the driver and driving conditions. In this paper we present a system which allows simultaneous capture of the driver's head pose, driving view, and surroundings of the vehicle. The integrated machine vision system utilizes a video stream of full 360 degree panoramic field of view. The processing modules include perspective transformation, feature extraction, head detection, head pose estimation, driving view synthesis, and motion segmentation. The paper presents a multi-state statistical decision models with Kalman filtering based tracking for head pose detection and face orientation estimation. The basic feasibility and robustness of the approach is demonstrated with a series of systematic experimental studies.

关键词： Vehicle driving Streaming media Magnetic heads Machine vision Face detection Telematics Feature extraction Motion detection Motion estimation Motion segmentation

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