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Recently, a model-based depth estimation technique has been proposed, which estimates surface model parameters by means of Hooke-Jeeves optimization. Assuming a parametric surface model, the parameters best explaining the perspective changes of the surface between different views are estimated. This constitutes a fitting of models directly into stereo images, which is in contrast to the usual approach...
In this paper, we propose an algorithm that recovers binocular disparities in accordance with the surface properties of the scene under consideration. To do so, we estimate the disparity as well as the normals in the disparity space, by setting the two tasks in a unified framework. A novel joint probabilistic model is defined through two random fields to favor both intra field (within neighboring...
In this paper, we present a new approach for recovering spacetime-consistent depth maps from multiple video sequences captured by stationary, synchronized and calibrated cameras for depth based free viewpoint video rendering. Our two-pass approach is generalized from the recently proposed region-tree based binocular stereo matching method. In each pass, to enforce temporal consistency between successive...
The aim of the stereo matching is to get the accurate disparity. But for the slanted and low textured plane, the ambiguity is increased. To get the more accurate disparity, most constraints are applied. In this paper, the statistical probability method (SPT) is applied to inferring disparity. The reliable confidence (RC) based on the SPT measures how the pixel disparity is reliable. The unreliable...
This paper presents a novel method for reconstructing high-quality video depth maps. A bundle optimization model is proposed to address the key issues, including image noise and occlusions, in stereo reconstruction. Our method not only uses the color constancy constraint, but also explicitly incorporates the geometric coherence constraint associating multiple frames in a video, thus can naturally...
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