To address perception problems we must be able to track dynamic objects of the environment. An important issue of tracking is the association problem in which we have to associate each new observation with one existing object in the environment. This problem is complex: unfortunately, the number of observations generally does not correspond to the number of objects. Moreover, the number of objects is difficult to estimate since one object might be temporarily occluded or unobserved simply because objects can enter or go out of ranges of vehicle sensors. Moreover, the perception sensors or the object detection process might generate false alarm measurements. In this paper, we propose a new solution to solve the multiple objects tracking problem, using the Viterbi algorithm (VA) [2]. It is an established optimisation technique for discrete Markovian systems that has been extensively used in speech recognition. In this paper, we present an extension of VA to solve multiple objects tracking in clutter environment and show some experimental results on multiple pedestrian tracking and also some quantitative comparisons with MHT algorithms.


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    Title :

    Multiple pedestrian tracking using Viterbi data association


    Contributors:
    Azim, A (author) / Aycard, O (author)


    Publication date :

    2010-06-01


    Size :

    1597311 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Multiple Pedestrian Tracking Using Viterbi Data Association, pp. 706-711

    Azim, A. / Aycard, O. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2010


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    Kraussling, A. / Schneider, F. E. / Sehestedt, S. et al. | British Library Conference Proceedings | 2006




    Off-Line Multiple Object Tracking using Candidate Selection and the Viterbi Algorithm

    Pitie, F. / Berrani, S.-A. / Kokaram, A. et al. | British Library Conference Proceedings | 2005