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This is a new approach to handle occlusions in stereovision algorithms in the multiview context using images destined for autostereoscopic displays. It takes advantage of information from all views and ensures the consistency of their disparity maps. We demonstrate its application in a correlation-based method and a graphcuts-based method. The latter uses a new energy, which merges both dissimilarities and occlusions evaluations. We discuss the results on real and virtual images.

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