An algorithm for disparity estimation with energy-based variational regularization using three image views is presented. In the new algorithm, dense disparity maps, including the disparity values for feature points, are first estimated by phase-based methods. Then a set of coupled partial differential equations (PDEs) are solved to refine these disparity maps together with the feature information. The visual appearance of the refined disparity is better than that of the results using similar variational regularization involving only one stereo pair of images. In addition, a new effective occlusion detection scheme is presented with good results.


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    Title :

    Three-view dense disparity estimation with occlusion detection


    Contributors:


    Publication date :

    2005-01-01


    Size :

    183555 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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