A model-based approach to vehicle tracking is proposed and applied to a highway trafic surveillance system, which is motivated by current research in intelligent transportation systems. Systems for traffic management and traveler information services require accurate and wide-area estimates of vehicle velocity and traffic spatial and temporal densities. A detection and tracking algorithm is developed that achieves good performance with complexity low enough for real-time implementation using inexpensive microprocessors. Detection thresholds are computed based on a statistical model for vehicle and background, and the theoretical detector performance is derived. The tracking algorithm filters position estimates from the detection algorithm using a simple vehicle dynamic model and the Kalman filter. Data association is accomplished with a nearest neighbor filter coupled with a lane-change handling logic.


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    Title :

    Model-based vehicle tracking from image sequences with an application to road surveillance


    Additional title:

    Modellbasierte Fahrzeugverfolgung durch Bildfolgenanalyse mit Bezug zur Überwachung von Autostraßen


    Contributors:

    Published in:

    Optical Engineering ; 35 , 6 ; 1723-1729


    Publication date :

    1996


    Size :

    7 Seiten, 2 Bilder, 1 Tabelle, 13 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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