We describe a vision-based vehicle detection and tracking method for forward collision warning in automobiles. The approach is based on a set of edge-based constraint filters that assist in the segmentation of vehicles from background clutter. The detected vehicles are then tracked using a combination of distance based matching, sum-of-square-of-difference in intensity (SSD) and edge density of detected vehicle regions. The computational load for tracking is minimized using a vehicle-clustering algorithm. Experimental results are presented to illustrate the performance of the algorithm.


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    Titel :

    Vision-based vehicle detection and tracking method for forward collision warning in automobiles


    Beteiligte:
    Srinivasa, N. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    444316 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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