Presents a method to determine the 3D motion of multiple objects from two perspective views. In our method, segmentation is determined based on a 3D rigidity constraint. We divide the input image into overlapping patches, and for each sample of the translation parameter space, we compute the rotation parameters of patches using a least-squares fit. Every patch votes for a sample in the translation and rotation parameter space. For a patch containing multiple motions, we use an M-estimator to compute rotation parameters of a dominant motion. We use the adaptive Hough transform to refine the relevant parameter space in a "coarse-to-fine" fashion. Applications of the proposed method to both synthetic and real images are demonstrated with promising results.<>


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    Titel :

    Recovering 3D motion of multiple objects using adaptive Hough transform


    Beteiligte:
    Tina Yu Tian (Autor:in) / Shah, M. (Autor:in)


    Erscheinungsdatum :

    01.01.1995


    Format / Umfang :

    602201 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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