In this paper, we propose a symmetric stereo model to handle occlusion in dense two-frame stereo. Our occlusion reasoning is directly based on the visibility constraint that is more general than both ordering and uniqueness constraints used in previous work. The visibility constraint requires occlusion in one image and disparity in the other to be consistent. We embed the visibility constraint within an energy minimization framework, resulting in a symmetric stereo model that treats left and right images equally. An iterative optimization algorithm is used to approximate the minimum of the energy using belief propagation. Our stereo model can also incorporate segmentation as a soft constraint. Experimental results on the Middlebury stereo images show that our algorithm is state-of-the-art.


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    Titel :

    Symmetric stereo matching for occlusion handling


    Beteiligte:
    Jian Sun, (Autor:in) / Yin Li, (Autor:in) / Kang, S.B. (Autor:in) / Heung-Yeung Shum, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    279295 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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