The detection of objects in every frame of a sequence is often not sufficient for scene interpretation. Tracking can increase the robustness, especially when occlusions occur or when objects temporarily disappear. In this paper we present a stochastic tracking approach which is based on the CONDENSATION algorithm (conditional density propagation over time) that is capable of tracking multiple objects with multiple hypotheses in range images. A probability density function describing the likely state of the objects is propagated over time using a dynamic model. The measurements influence the probability function and allow the incorporation of new objects into the tracking scheme. Additionally, the representation of the density function with a fixed number of samples ensures a constant running time per iteration step. Results with data from different sources are shown for automotive applications.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Tracking cars in range images using the CONDENSATION algorithm


    Contributors:
    Meier, E.B. (author) / Ade, F. (author)


    Publication date :

    1999-01-01


    Size :

    631475 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Tracking Cars in Range Images Using the Condensation Algorithm

    Meier, E. B. / Ade, F. / IEEE et al. | British Library Conference Proceedings | 1999


    Tracking cars in range image sequences

    Meier, E.B. / Ade, F. | IEEE | 1997


    Our cars: Range Rover Sport

    McNamara,P. / Land Rover,GB | Automotive engineering | 2007


    Our cars: Range Rover TDV8

    Hallet,C. / Land Rover,GB | Automotive engineering | 2011


    Cars Tracking and Counting at Night

    Chen, Yuan Been | Trans Tech Publications | 2012