This paper describes a vehicle detection method using 3D data derived from a disparity map available in realtime. The integration of a flat road model reduces the search space in all dimensions. Inclination changes are considered for the road model update. The vehicles, modeled as a cuboid, are detected in an iterative refinement process for hypotheses generation on the 3D data. The detection of a vehicle is performed by a mean-shift clustering of plane fitted segments potentially belonging together in a first step. In the second step a u/v-disparity approach generates vehicle hypotheses covering differently appearing vehicles. The system was evaluated in real-traffic-scenes using a Global Positioning System (GPS).


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    Titel :

    Stereo vision based vehicle detection


    Beteiligte:
    Kormann, Benjamin (Autor:in) / Neve, Antje (Autor:in) / Klinker, Gudrun (Autor:in) / Stechele, Walter (Autor:in)


    Erscheinungsdatum :

    2010


    Format / Umfang :

    8 Seiten, 18 Quellen



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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