This paper presents a probabilistic framework for off-line multiple object tracking. At each timestep, a small set of deterministic candidates is generated which is guaranteed to contain the correct solution. Tracking an object within video then becomes possible using the Viterbi algorithm. In contrast with particle filter methods where candidates are numerous and random, the proposed algorithm involves a few candidates and results in a deterministic solution. Moreover, we consider here off-line applications where past and future information is exploited. This paper shows that, although basic and very simple, this candidate selection allows the solution of many tracking problems in different real-world applications and offers a good alternative to particle filter methods for off-line applications.


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    Title :

    Off-line multiple object tracking using candidate selection and the Viterbi algorithm


    Contributors:
    Pitie, F. (author) / Berrani, S.-A. (author) / Kokaram, A. (author) / Dahyot, R. (author)


    Publication date :

    2005-01-01


    Size :

    253261 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    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


    TRACKING MULTIPLE OBJECTS USING THE VITERBI ALGORITHM

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




    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