This paper addresses the problem of vehicle tracking under a single static, uncalibrated camera without any constraints on the scene or on the motion direction of vehicles. We introduce an explicit contour model, which not only provides a good approximation to the contours of all classes of vehicles but also embeds the contour dynamics in its parameterized template. We integrate the model into a Bayesian framework with multiple cues for vehicle tracking, and evaluate the correctness of a target hypothesis, with the information implied by the shape, by monitoring any conflicts within the hypothesis of every single target as well as between the hypotheses of all targets. We evaluated the proposed method using some real sequences, and demonstrated its effectiveness in tracking vehicles, which have their shape changed significantly while moving on curly, uphills roads. © 2005 IEEE. ; published_or_final_version ; The IEEE International Conference on Image Processing (ICIP 2005), Genoa, Italy, 11-14 September 2005. In Proceedings of IEEE-ICIP, 2005, v. 2, p. 582-585


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    Title :

    Explicit contour model for vehicle tracking with automatic hypothesis validation


    Contributors:
    Wong, KYK (author) / Chin, FYL (author) / Chung, RHY (author) / Yiu, BWS (author)

    Publication date :

    2005-01-01



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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