In a known environment, objects may be tracked in multiple views using a set of background models. Stereo-based models can be illumination-invariant, but often have undefined values which inevitably lead to foreground classification errors. We derive dense stereo models for object tracking using long-term, extended dynamic-range imagery, and by detecting and interpolating uniform but unoccluded planar regions. Foreground points are detected quickly in new images using pruned disparity search. We adopt a "late-segmentation" strategy, using an integrated plan-view density representation. Foreground points are segmented into object regions only when a trajectory is finally estimated, using a dynamic programming-based method. Object entry and exit are optimally determined and are not restricted to special spatial zones.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Plan-view trajectory estimation with dense stereo background models


    Contributors:


    Publication date :

    2001-01-01


    Size :

    893536 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Plan-View Trajectory Estimation with Dense Stereo Background Models

    Darrell, T. / Demirdjian, D. / Checka, N. et al. | British Library Conference Proceedings | 2001


    Handling occlusions in dense multi-view stereo

    Sing Bing Kang, / Szeliski, R. / Jinxiang Chai, | IEEE | 2001


    Handling Occlusions in Dense Multi-View Stereo

    Kang, S. B. / Szeliski, R. / Chai, J. et al. | British Library Conference Proceedings | 2001


    Plan View Display (PVD) Background Lighting

    P. C. Gustafson / J. Aschenbach / R. L. Sulzer | NTIS | 1976


    Multi-View Stereo Reconstruction of Dense Shape and Complex Appearance

    Jin, H. / Soatto, S. / Yezzi, A. J. | British Library Online Contents | 2005