This paper presents a new approach for pedestrian detection in the vehicle environment using stereo vision. The segmented pedestrians, represented as a set of equal disparity attributed segments, are refined using B-spline arithmetic. These segments are obtained from a non-dense disparity map. The disparity map is estimated using a new developed algorithm relying on the contour-following algorithm. The approximated segments are then matched with preexisting pedestrian model. The pedestrian model is generated by utilizing B-spline functions, which can refine the human body contour extracted in a digitized image. Some attributes of the approximated segments like concavity, convexity, and local curvature are considered to perform the matching process.


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    Title :

    Stereo vision based pedestrian detection using B-spline modeling


    Contributors:


    Publication date :

    2008-09-01


    Size :

    230392 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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