A Hybrid Genetic Approach for Stereo Matching

被引：0
|
作者：
Kiperwasser, Eliyahu [1 ]
David, Omid [1 ]
Netanyahu, Nathan S. [1 ]
机构：
[1] Bar Ilan Univ, Dept Comp Sci, IL-52900 Ramat Gan, Israel
来源：
GECCO'13: PROCEEDINGS OF THE 2013 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE | 2013年
关键词：
Computer Vision; Genetic Algorithm; Stereo Matching;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we present a genetic algorithm (GA)-based approach for the stereo matching problem. More precisely, the approach presented is a combination of a simple dynamic programming algorithm, commonly used for stereo matching, with a practical GA-based optimization scheme. The performance of our scheme was evaluated on standard test data of the Middlebury benchmark [1]. Specifically, the number of incorrect disparities on these data decreases by approximately 20% in comparison to the original approach (without the use of a GA).
引用
收藏
页码：1325 / 1331
页数：7
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