This paper describes an approach to reformulating the stereo matching problem as a large scale Linear Program. The approach proceeds by approximating the match cost function associated with each pixel with a piecewise linear convex function. Regularization terms related to the first and second derivative of the disparity field are also captured with piecewise linear penalty terms. The resulting large scale linear program can be tackled using interior point methods and the associated Newton Steps involve matrices that reflect the structure of the underlying pixel grid. The proposed scheme effectively exploits the structure of these matrices to solve these linear systems efficiently
Binocular stereovision is based on the process of obtaining the depth information from a pair of lef...
Stereo matching algorithms are one of heavily researched topic in binocular stereo vision. Massive 3...
: A new method for solving the stereo matching problem in the presence of large occlusion is present...
We present a convex optimization approach to dense stereo matching in computer vision. Instead of di...
We present a novel convex-optimization approach to solving the dense stereo matching problem in comp...
International audienceThis paper addresses the problem of dense disparity estimation from a pair of ...
This paper describes a novel approach to recovering a parametric deformation that optimally register...
This paper describes a novel approach to recovering a parametric deformation that optimally register...
Abstract: A new method for solving the stereo matching problem in the presence of large occlusion is...
The correspondence problem in stereo vision is to calculate matches between pixels (points) or featu...
Abstract—This paper addresses the problem of dense disparity estimation from a pair of color stereo ...
International audienceThis paper addresses the problem of dense disparity estimation from a pair of ...
86 p.Stereo matching involves the estimation of depth from two or more images of the same scene take...
Binocular stereovision is based on the process of obtaining the depth information from a pair of lef...
Binocular stereovision is based on the process of obtaining the depth information from a pair of lef...
Binocular stereovision is based on the process of obtaining the depth information from a pair of lef...
Stereo matching algorithms are one of heavily researched topic in binocular stereo vision. Massive 3...
: A new method for solving the stereo matching problem in the presence of large occlusion is present...
We present a convex optimization approach to dense stereo matching in computer vision. Instead of di...
We present a novel convex-optimization approach to solving the dense stereo matching problem in comp...
International audienceThis paper addresses the problem of dense disparity estimation from a pair of ...
This paper describes a novel approach to recovering a parametric deformation that optimally register...
This paper describes a novel approach to recovering a parametric deformation that optimally register...
Abstract: A new method for solving the stereo matching problem in the presence of large occlusion is...
The correspondence problem in stereo vision is to calculate matches between pixels (points) or featu...
Abstract—This paper addresses the problem of dense disparity estimation from a pair of color stereo ...
International audienceThis paper addresses the problem of dense disparity estimation from a pair of ...
86 p.Stereo matching involves the estimation of depth from two or more images of the same scene take...
Binocular stereovision is based on the process of obtaining the depth information from a pair of lef...
Binocular stereovision is based on the process of obtaining the depth information from a pair of lef...
Binocular stereovision is based on the process of obtaining the depth information from a pair of lef...
Stereo matching algorithms are one of heavily researched topic in binocular stereo vision. Massive 3...
: A new method for solving the stereo matching problem in the presence of large occlusion is present...