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Superpixels have become very popular in many computer vision applications.Nevertheless, they remain underexploited since the superpixel decomposition mayproduce irregular and non stable segmentation results due to the dependency tothe image content. In this paper, we first introduce a novel structure, asuperpixel-based patch, called SuperPatch. The proposed structure, based onsuperpixel neighborhood, leads to a robust descriptor since spatial informationis naturally included. The generalization of the PatchMatch method toSuperPatches, named SuperPatchMatch, is introduced. Finally, we propose aframework to perform fast segmentation and labeling from an image database, anddemonstrate the potential of our approach since we outperform, in terms ofcomputational cost and accuracy, the results of state-of-the-art methods onboth face labeling and medical image segmentation.

SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches