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Motion Estimation via Belief Propagation

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4 Author(s)

We present a probabilistic model for motion estimation in which motion characteristics are inferred on the basis of a finite mixture of motion models. The model is graphically represented in the form of a pairwise Markov random field network upon which a Loopy belief propagation algorithm is exploited to perform inference. Experiments on different video clips are presented and discussed.

Published in:

Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on

Date of Conference:

10-14 Sept. 2007