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<p><b>Abstract</b>—This paper presents the application of a very efficient multiresolution transformation, which is related to the renormalization group approach of physics, to the problem of motion segmentation. The proposed approach is much faster and yields much better results than the full resolution approach. The problem is formulated as one of global optimization where a cost function is constructed to combine the information obtained by various processors as well as the constraints we impose to the problem. The cost function is optimized using the supercoupling multiresolution approach.</p>
Motion analysis, motion segmentation, supercoupling approach, Markov random fields, stochastic relaxation.

J. Kittler, M. Petrou and M. Bober, "Nonlinear Motion Estimation Using the Supercoupling Approach," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 20, no. , pp. 550-555, 1998.
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