A CONVEX-OPTIMIZATION APPROACH TO DENSE STEREO MATCHING

被引：0

作者：

Li, Yujun ^{[1
]}

Au, Oscar C. ^{[1
]}

Xu, Lingfeng ^{[1
]}

Sun, Wenxiu ^{[1
]}

Chui, Sung-Him ^{[1
]}

Kwok, Chun-Wing ^{[1
]}

机构：

[1] Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Kowloon, Hong Kong, Peoples R China

来源：

2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年

关键词：

disparity estimation; stereo matching; convex optimization; surface reconstruction; computer vision;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We present a novel convex-optimization approach to solving the dense stereo matching problem in computer vision. Instead of directly solving for disparities of pixels, by establishing the connection between a permutation matrix and a disparity vector, we directly formulate the stereo matching problem as a continuous convex quadratic program in a simple, elegant and straight forward manner without performing any complicated relaxation or approximation. By using CVX, the Matlab software for disciplined convex programming, our method is extremely simple to implement.

引用

页码：1005 / 1008

页数：4

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