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Empirical Bayesian motion segmentation

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2 Author(s)
N. Vasconcelos ; Compaq Comput. Corp., Cambridge, MA, USA ; A. Lippman

We introduce an empirical Bayesian procedure for the simultaneous segmentation of an observed motion field and estimation of the hyperparameters of a Markov random field prior. The new approach exhibits the Bayesian appeal of incorporating prior beliefs, but requires only a qualitative description of the prior, avoiding the requirement for a quantitative specification of its parameters. This eliminates the need for trial-and-error strategies for the determination of these parameters and leads to better segmentations

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:23 ,  Issue: 2 )