We present a multiscale method for motion segmentation. Our method begins with local, ambiguous optical flow measurements. It uses a process of aggregation to resolve the ambiguities and reach reliable estimates of the motion. In addition, as the aggregation process proceeds and larger aggregates are identified it employs a progressively more complex model to describe the motion. In particular, we proceed by recovering translational motion at fine levels, through affine transformation at intermediate levels, to 3D motion (described by a fundamental matrix) at the coarsest levels. Finally, the method is integrated with a segmentation method that uses intensity cues. We further demonstrate the utility of the method on both random dot and real motion sequences.


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    Titel :

    Multiscale segmentation by combining motion and intensity cues


    Beteiligte:
    Meirav Galun, (Autor:in) / Alexander Apartsin, (Autor:in) / Ronen Basri, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    851409 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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