This paper presents a method for pedestrian detection and tracking using a single 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 (e.g., grayscale SVM recognition versus binary SVM recognition and entire-body detection versus upper-body detection) have been carried out to illustrate the feasibility of our approach.


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    Title :

    Pedestrian detection and tracking with night vision


    Contributors:
    Fengliang Xu, (author) / Xia Liu, (author) / Fujimura, K. (author)


    Publication date :

    2005-03-01


    Size :

    4060077 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Pedestrian Detection and Tracking with Night Vision

    Xu, F. / Fujimura, K. / INRIA et al. | British Library Conference Proceedings | 2003


    Pedestrian Detection and Tracking With Night Vision

    Xu, F. / Liu, X. / Fujimura, K. et al. | British Library Conference Proceedings | 2005


    Pedestrian detection and tracking with night vision

    Fengliang Xu, / Kikuo Fujimura, | IEEE | 2002


    Pedestrian detection using stereo night vision

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    Pedestrian Detection Using Stereo Night Vision

    Liu, X. / Fujimura, K. / IEEE | British Library Conference Proceedings | 2003