This paper presents a method for pedestrian detection and tracking using a night vision video camera installed on the vehicle. To deal with the nonrigid nature of human appearance on the road, a two-step detection/tracking method is proposed. The detection phase is performed by a support vector machine (SVM) with size-normalized pedestrian candidates and the tracking phase is a combination of Kalman filter prediction and mean shift tracking. The detection phase is further strengthened by information obtained by a road detection module that provides key information for pedestrian validation. Experimental comparisons have been carried out on gray-scale SVM recognition vs. binary SVM recognition and entire body detection vs. upper body detection.


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    Title :

    Pedestrian detection and tracking with night vision


    Contributors:

    Published in:

    Publication date :

    2002-01-01


    Size :

    900210 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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