Generating vehicle trajectories from video data is an important application of ITS (intelligent transportation systems). We introduce a new tracking approach which uses model-based 3-D vehicle detection and description algorithm. Our vehicle detection and description algorithm is based on a probabilistic line feature grouping, and it is faster (by up to an order of magnitude) and more flexible than previous image-based algorithms. We present the system implementation and the vehicle detection and tracking results.


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    Titel :

    Fast vehicle detection with probabilistic feature grouping and its application to vehicle tracking


    Beteiligte:
    Kim, (Autor:in) / Malik, (Autor:in)


    Erscheinungsdatum :

    01.01.2003


    Format / Umfang :

    759682 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Fast Vehicle Detection with Probabilistic Feature Grouping and its Application to Vehicle Tracking

    Kim, Z. / Malik, J. / IEEE | British Library Conference Proceedings | 2003


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