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

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

引用

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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A novel interactivity environment for integrated intelligent transportation and telematic systems 5

A novel interactivity environment for integrated intelligent...

引用

5th IEEE International Conference on Intelligent Transportation Systems, ITSC 2002

作者： Hall, T. Brett Trivedi, Mohan M. Computer Vision and Robotics Research Laboratory University of California San DiegoCA92093-0407 United States

ISBN: (纸本)0780373898

Advances in intelligent transportation are rapidly sensing and connecting both highways and vehicles. This recent availability of high-speed communication and large quantities of information are rapidly changing the way we perceive transportation. In order to develop technologies and applications that are practical in this intelligent environment, it is important to consider specific ways to best use this infrastructure effectively. This paper focuses on the development of and experiments with a visualization environment that presents an interactive, immersive, and context-preserving display of outdoor information. The developed visualization integrates a variety of types of information about a section of interstate such as aerial photographs, maps, and live outdoor videos into a single interactive environment. Additionally, a wireless mobile testbed is presented that allows the undertaking of novel interactivity experiments among mobile participants without requiring a fully instrumented vehicle. These systems allow effective experimentation with and integration between highway and vehicle based real-world intelligent transportation systems. © 2002 IEEE.

关键词： Vehicles

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Real-time wide area tracking: Hardware and software infrastructure 5

Real-time wide area tracking: Hardware and software infrastr...

引用

5th IEEE International Conference on Intelligent Transportation Systems, ITSC 2002

作者： Kogut, Greg T. Trivedi, Mohan M. Computer Vision and Robotics Research Laboratory University of California San DiegoCA92093-0407 United States

ISBN: (纸本)0780373898

In recent years, large number of cameras have been installed in freeway and road environments. While the use of some of these cameras is being automated through computer vision, few computer vision systems allow for true wide-area large scaled automation. This paper describes a distributed computing system capable of managing an arbitrarily large sensor network using only common computing and networking platforms. The architecture is capable of handling many common computer vision tasks, as well as the inter-sensor communication necessary for developing new algorithms which employ data from multiple sensors. This system is tested with an algorithm which tracks moving objects through a prototype camera network with non-overlapping fields of view in a college campus environment. This algorithm allows the system to maintain the identity of a tracked objects as it leaves find enters the fields of view of individual sensors. Such an algorithm is necessary for applications which require tracking objects over large distances or over long periods of time in an environment without complete sensor coverage. © 2002 IEEE.

关键词： computer vision

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Distributed interactive video arrays for event based analysis of incidents 5

Distributed interactive video arrays for event based analysi...

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5th IEEE International Conference on Intelligent Transportation Systems, ITSC 2002

作者： Trivedi, Mohan M. Prati, Andrea Kogut, Greg Computer Vision and Robotics Research Laboratory University of California at San Diego San DiegoCA92093-0434 United States

ISBN: (纸本)0780373898

The Distributed Interactive Video Array (DIVA) system is developed to provide a large-scale, redundant cluster of video streams to observe a remote scene and to supply automatic focus of-attentian with event-driven serving to capture desired events at appropriate resolutions and perspectives. Installing multiple sensors introduces several new research issues related to the system design, including handoff schemes for passing tracked objects between sensors and clusters, methods for determining the "best view" given the context of the traffic scene, and sensor fusion algorithms to best employ the strengths of a given sensor or sensor modality. This paper describes our research focused on the development of DIVA system for traffic and incident monitoring. The paper describes the overall architecture of the DIVA system. Algorithms (or vehicle and platoon tracking using multiple cameras, and experimental results using novel distributed video networks deployed on the campus and the interstate 1-5. © 2002 IEEE.

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Real-time wide area tracking: hardware and software infrastructure

Real-time wide area tracking: hardware and software infrastr...

引用

International Conference on Intelligent Transportation

作者： G.T. Kogut M.M. Trivedi The Computer Vision And Robotics Research Laboratory University of California La Jolla CA USA

In recent years, large number of cameras have been installed in freeway and road environments. While the use of some of these cameras is being automated through computer vision, few computer vision systems allow for true wide-area large scaled automation. This paper describes a distributed computing system capable of managing an arbitrarily large sensor network using only common computing and networking platforms. The architecture is capable of handling many common computer vision tasks, as well as the inter-sensor communication necessary for developing new algorithms which employ data from multiple sensors. This system is tested with an algorithm which tracks moving objects through a prototype camera network with non-overlapping fields or view in a college campus environment This algorithm allows the system to maintain the identity of a tracked objects as it leaves and enters the fields of view of individual sensors. Such an algorithm is necessary for applications which require tracking objects over large distances or over long periods of time in an environment without complete sensor coverage.

关键词： Hardware Cameras computer vision Distributed computing Sensor systems Traffic control Roads Automation computer network management Sensor phenomena and characterization

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Streaming face recognition using multicamera video arrays

Streaming face recognition using multicamera video arrays

引用

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 novel interactivity environment for integrated intelligent transportation and telematic systems

A novel interactivity environment for integrated intelligent...

引用

International Conference on Intelligent Transportation

作者： T.B. Hall M.A. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

关键词： Intelligent transportation systems Telematics Intelligent vehicles Road transportation Road vehicles Visualization Joining processes Displays Videos Testing

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Distributed interactive video arrays for event based analysis of incidents

Distributed interactive video arrays for event based analysi...

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International Conference on Intelligent Transportation

作者： M.M. Trivedi A. Prati G. Kogut Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

The distributed interactive video array (DIVA) system is developed to provide a large-scale, redundant cluster of video streams to observe a remote scene and to supply automatic focus-of-attention with event-driven servoing to capture desired events at appropriate resolutions and perspectives. Installing multiple sensors introduces several new research issues related to the system design, including handoff schemes for passing tracked objects between sensors and clusters, methods for determining the "best view" given the context of the traffic scene, and sensor fusion algorithms to best employ the strengths of a given sensor or sensor modality. This paper describes our research focused on the development of DIVA system for traffic and incident monitoring. The paper describes the overall architecture of the DIVA system. Algorithms for vehicle and platoon tracking using multiple cameras, and experimental results using novel distributed video networks deployed on the campus and the interstate I-5.

关键词： Sensor fusion Sensor systems Layout Large-scale systems Streaming media Clustering algorithms Telecommunication traffic Monitoring Vehicles Cameras

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Maintaining the identity of multiple vehicles as they travel through a video network

Maintaining the identity of multiple vehicles as they travel...

引用

IEEE Workshop on Multi-Object Tracking

作者： G.T. Kogut M.M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

ISBN: (纸本)0769511716

Large vision infrastructures have been installed, or are under construction in many major metropolitan areas. These networks of cameras offer enormous volumes of data from large areas. However, most work in ITS computer vision is constricted to the use of either single cameras, or small numbers of cameras. There is an enormous amount of information available from the fusion of data from multiple cameras that is not available from any single sensor. This paper presents an algorithm that provides an example of such data fusion: maintaining the identity of a vehicle, or groups of vehicles as they pass through multiple cameras sites. The algorithm uses a combination of color features and the spatial organization of vehicles within platoons to minimize false positives. The algorithm could be used in an application to track individual cars as they travel long distances through a traffic system allowing the measurement of point-to-point traffic parameters, such as travel time.

关键词： Cameras Telecommunication traffic Vehicle detection Costs Sensor systems Hardware Traffic control Bandwidth Internet Fuses

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