计算机工程与应用2020，Vol.56Issue(1)：216-223,8.DOI:10.3778/j.issn.1002-8331.1810-0044
融合多特征表示和超像素优化的双目立体匹配
Binocular Stereo Matching with Multi-feature Representation and Super-pixel Optimization
郭倩 1张福杨 1孙农亮1
作者信息
- 1. 山东科技大学 电子通信与物理学院,山东 青岛 266590
- 折叠
摘要
Abstract
Aiming at the accuracy problems in texture lacking region, occlusion region and depth discontinuous in binocular stereo matching, an algorithm based on multi-feature representation and super-pixel optimization is proposed. By adding edge information into initial cost calculating, and combining with image local information, it can improve the edge region recognition in disparity calculation. In cost aggregation step, the initial aggregation region is computed by simple linear iterative clustering method. In order to aggregate much more information in texture lacking region, an algorithm of adaptive searching based on the rice skeleton is proposed. In disparity optimization step, using the initial super-pixel region, to correct disparities which are mismatched. Experiments on the Middlebury stereoscopic dataset test platform prove that the proposed algorithm has higher accuracy.关键词
双目立体匹配/多特征表示/超像素分割/超像素优化/机器视觉Key words
binocular stereo matching/multi-feature representation/super-pixel segmentation/super-pixel optimization/computer vision分类
信息技术与安全科学引用本文复制引用
郭倩,张福杨,孙农亮..融合多特征表示和超像素优化的双目立体匹配[J].计算机工程与应用,2020,56(1):216-223,8.
