Finding reliable and well distributed keypoint correspondences between images of non-static scenes is an important task in Computer Vision. We present an iterative algorithm that improves a descriptor Based matching result by enforcing local smoothness. During the optimization process, a Delaunay triangulation of the current set of matches is dynamically maintained. This 2D mesh provides natural neighborhoods and local affine transformations that are used to remove outliers and to resolve ambiguities. The optimization results in a decrease of incorrect correspondences and a significant increase in the total number of matches. The runtime of the overall algorithm is by far dictated by the descriptor Based matching.
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