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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    Title :

    Multiscale segmentation by combining motion and intensity cues


    Contributors:


    Publication date :

    2005-01-01


    Size :

    851409 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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