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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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A multimodal framework for vehicle and traffic flow analysis

A multimodal framework for vehicle and traffic flow analysis

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International Conference on Intelligent Transportation

作者： J. Ploetner M.M. Trivedi Computer Vision and Robotics Research Laboratory CVRR University of California San Diego La Jolla CA USA

This paper presents an overview of a novel multimodal system being developed at UC San Diego for vehicle detection and traffic flow analysis. A distributed multimodal array (DiMMA) framework is presented for sensory data acquisition, processing, analysis, fusion, and "active" control mechanisms needed to recognize objects, events, and activities which have multi-modal signatures. Current sensing modalities being researched include video, audio, seismic, magnetic, and passive infrared. Feature extraction and data fusion techniques are being investigated to improve robustness and study the advantages and disadvantages of each sensing modality. Preliminary results of this rapidly deployable system are discussed, along with possible future expansions, including laser range scanners, geophones, pneumatic road tubes, and traditional inductive loops

关键词： Vehicle detection Road vehicles Monitoring Robustness Sensor arrays Magnetic analysis Traffic control Information security Detectors Cameras

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3D Shape Context Based Gesture Analysis Integrated with Tracking using Omni Video Array

3D Shape Context Based Gesture Analysis Integrated with Trac...

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

作者： Kohsia S. Huang M.M. Trivedi Computer Vision and Robotics Research (CVRR) Laboratory University of California San Diego USA

In this paper we introduce a multilayer cylindrical histogram based feature space for representing 3D shape context of human body. Dynamics of gestures are analyzed using discrete hidden Markov models (DHMM) with quantized feature vectors. Extensive experimental trials with multiple subjects and a range of gesture classes are presented. Gesture recognition accuracies of over 85% (for nine gestures, and 9 subjects) and over 95% (for seven gestures) support the basic feasibility and robustness of the approach.

关键词： Shape Humans Hidden Markov models Biological system modeling Cameras Robustness Context modeling Information analysis Pattern analysis computer vision

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computer vision for homeland security: a perspective on its promise and pitfalls

Computer vision for homeland security: a perspective on its ...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

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

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A track-based human movement analysis and privacy protection system adaptive to environmental contexts

A track-based human movement analysis and privacy protection...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Sangho Park M.M. Trivedi Computer Vision and Robotics Research (CVRR) Laboratory University of California San Diego La Jolla CA USA

This paper presents a track-based system for human movement analysis and privacy protection. Our system is adaptive to environmental contexts such as illumination variations, complex moving cast shadows, different camera perspectives, and diverse sue scenarios. Most of outdoor surveillance systems have been targeting at specific environmental situation: i.e., specific time, place, and activity scenarios. We address that more general human movement analysis systems should be able to handle multiple heterogeneous situations in an adaptive manner. We introduce the concept of "spatio-temporal personal boundary" to represent different grouping patterns of human tracks, and we incorporate the concept with various site models. Experimental evaluations with extensive outdoor data show our system's robustness to environmental changes and effectiveness to properly handle various environmental contexts.

关键词： Privacy Protection Adaptive systems Biomedical monitoring Humans Surveillance Layout Robot vision systems Target tracking Cameras

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Distributed omni-video arrays and digital tele-viewer for customized viewing, event detection and notification

Distributed omni-video arrays and digital tele-viewer for cu...

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International Conference on Information Technology: Coding and Computing (ITCC)

作者： M.M. Trivedi K.S. Huang Tarak Gandhi B. Hall K. Harlow Computer Vision and Robotics Research (CVRR) Laboratory University of California San Diego USA

Recent innovations in real-time machine vision, distributed computing, software architectures, and encrypted high-speed networking are expanding the available technology for intelligent camera arrays on televiewing and interactive applications. In this paper we describe research aimed at the realization of a powerful televiewing system using arrays of omnidirectional cameras. The video arrays provide an interactive, real-time, multiresolution televiewing interface to multiple people including physical security and emergency response crews simultaneously. Security measures such as authentication and network encryption are implemented on multiple platforms. Fusion of high-resolution rectilinear image over the omnidirectional image is also carried out. computer vision techniques based on motion analysis are used for detecting interesting events. The televiewing system is verified for the performance as well as physically tested on the Super Bowl 2003 event for crowd detection and traffic monitoring.

关键词： Event detection Cryptography Cameras Power system security Technological innovation Machine vision Distributed computing Software architecture High-speed networks Intelligent networks

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Distributed video arrays for tracking, human identification, and activity analysis

Distributed video arrays for tracking, human identification,...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： K.S. Huang M.M. Trivedi Computer Vision and Robotics Research CVRR Laboratoly University of California San Diego USA

In this paper we discuss the intelligent or smart camera based systems for capturing visual contextual information at multiple levels of information abstraction. A distributed video array, with multiple omnidirectional and rectilinear cameras, is used to acquire visual information. System architecture as well as 3D tracking and human identification modules are described. Examples of the use of distributed video arrays in indoor, outdoor, and mobile environments are presented.

关键词： Humans Smart cameras Robustness Information analysis Intelligent robots Robot vision systems Intelligent sensors Microphone arrays Signal resolution Event detection

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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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Streaming face recognition using multicamera video arrays

Streaming face recognition using multicamera video arrays

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International Conference on Pattern Recognition

作者： K.S. Huang M.M. Trivedi Computer Vision and Robotics Research (CVRR) Laboratory University of California San Diego USA

We present face recognition schemes based on video streams: the majority decision rule and HMM maximum likelihood (ML) decision rules. PCA type of subspace feature analysis is first applied to the face images in a video segment of a fixed number of frames. The majority decision rule is then applied to PCA recognition results in the video segment. Discrete HMM (DHMM) is also applied to the single-frame recognition sequences. Continuous density HMM (CDHMM) is applied directly to the sequence of PCA feature vectors for ML decision on the video segment in a delayed decision manner. Experimental results are compared between these three schemes in terms of the number of states and Gaussian mixtures of the HMMs. CDHMM-based decision rule achieved a 99% correct recognition rate in average. A geometric interpretation of ML in the feature subspace well explains the observed performances.

关键词： Streaming media Face recognition Hidden Markov models Principal component analysis Image segmentation Lighting Testing computer vision Humans Covariance matrix

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A televiewing system for multiple simultaneous customized perspectives and resolutions

A televiewing system for multiple simultaneous customized pe...

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International Conference on Intelligent Transportation

作者： B. Hall Kohsia Huang M. Trivedi Computer Vision and Robotics Research Laboratory CVRR University of California La Jolla CA USA

Recent innovations in real-time machine vision, distributed computing, software architectures and high-speed communication are expanding the available technology for intelligent system development. These technologies allow the realization of intelligent systems that provide the capabilities for a user to experience events from remote locations in an interactive way. In this paper, we describe research aimed at the realization of a powerful televiewing system applied to the traffic incident detection and monitoring needs of today's highways. Sensor clusters utilizing both rectilinear and omni-directional cameras provide an interactive, real-time, multi-resolution televiewing interface to emergency response crews. Ultimately, this system will have a direct impact on reducing incident-related highway congestion by improving the quality of information to which emergency personnel have access.

关键词： Intelligent systems Machine intelligence Intelligent sensors Road transportation Technological innovation Real time systems Machine vision Distributed computing Software architecture Remote monitoring

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