Stochastic approach for motion vector estimation in video coding

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Abstract
Motion vector (MV) estimation plays an important role in motion compensated video coding. We propose in this research a new fast MV estimation algorithm by using a statistical approach. Our algorithm consists of two components. First, instead of using a fixed search window centered at the origin, we allow the center and the size of the search window to vary according to the motion vectors obtained in coding previous frames. Second, instead of performing an exhaustive block matching within the search window, we introduce a probability density function which has a peak at the window center and decays as the distance becomes larger, and we generate a few search positions according to the probability density. Experiments are performed to illustrate the excellent performance of the proposed algorithm.

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