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Disparity estimation constitutes an active research area in stereo vision, and in recent years, global estimation methods aiming at minimizing an energy function over the whole image have gained a lot of attention. To overcome the difficulties raised by the nonconvexity of the minimized criterion, convex relaxations have been proposed by several authors. In this paper, the global energy function is...
The Non-Local Total Variation (NLTV) has been recently formalized to define new functionals for signal and image analysis, that strictly fit into the widely used variational framework but overcome the locality limitation of the classical TV. This work lies in the context of disparity estimation in a variational framework, where Total Variation represents a common tool to impose a smooth behavior to...
In multiview video representation, one of the most popular format is the so-called multiple view video plus depth. This representation is made up of N image sequences, each accompanied by a sequence of depth maps, telling the distance of each represented pixel from the observing camera. The depth maps are needed at the decoder side in order to generate intermediate views and therefore to enrich the...
Stereo matching is an active area of research in image processing. In a recent work, a convex programming approach was developed in order to generate a dense disparity field. In this paper, we address the same estimation problem and propose to solve it in a more general convex optimization framework based on proximal methods. More precisely, unlike previous works where the criterion must satisfy some...
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