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In this paper we discuss a hybrid technique for piecewisesmooth optical flow estimation. We first pose optical flow estimation as a gradient-based local regression problem and solve it under a high-breakdown robust criterion. Then taking the output from the first step as the initial guess, we recast the problem in a robust matching-based global optimization framework. We have developed novel fastconverging deterministic algorithms for both optimization problems and incorporated a hierarchicaldoi:10.1109/cvpr.2001.991034 dblp:conf/cvpr/YeH01 fatcat:yttmbhftkrenxlylktw3pxgpzm