Abstract
A probabilistic relaxation technique for high accuracy disparity estimation is proposed. The relaxation rule is defined according to the likelihood that estimates obey physically meaningful constraints. High accuracy is achieved by applying the approach to points inside salient image areas previously approximated by second-order polynomials.
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