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Poster BMVC 2006. Constrained Diffusion and Some Applications: Low Baseline Stereo and Video Segmentation

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Version 2 2013-12-16, 09:14
Version 1 2013-12-16, 10:11
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posted on 2013-12-16, 10:11 authored by Gabriele FaccioloGabriele Facciolo, Federico Lecumberry, Andrés Almansa, Alvaro Pardo, Vicent Caselles, Bernard Rougé

Minimal surface regularization has been used in several applications ranging from stereo to image segmentation, sometimes hidden as a graph-cut discrete formulation, or as a strictly convex approximation to TV minimization. In this paper we consider a modified version of minimal surface regularization coupled with a robust data fitting term for interpolation purposes, where the corresponding evolution equation is constrained to diffuse only along the isophotes of a given image u and we design a convergent numerical scheme to accomplish this. To illustrate the usefulness of our approach, we apply this framework to the digital elevation model interpolation and to constrained vector probability diffusion.

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