[1]陈佳坤 罗谦 曾玉林.一种用于立体图像匹配的改进稀疏匹配算法[J].计算机技术与发展,2011,(10):63-65.
　CHEN Jia-kun,LUO Qian,ZENG Yu-lin.An Improved Sparse Matching Algorithm for Stereo Matching[J].,2011,(10):63-65.
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一种用于立体图像匹配的改进稀疏匹配算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2011年10期
页码:
63-65
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
An Improved Sparse Matching Algorithm for Stereo Matching
文章编号:
1673-629X（2011）10-0063-03
作者:
陈佳坤1 罗谦2 曾玉林1
[1]西南交通大学信息科学与技术学院[2]中国民用航空局第二研究所
Author(s):
CHEN Jia-kun ;  LUO Qian;  ZENG Yu-lin
[1]School of Information Science and Technology, Southwest Jiaotong University[2]The Second Research Institute of CAAC
关键词:
立体匹配; 置信传播; 图像重建
Keywords:
stereo vision;  belief propagation ; image reconstruction
分类号:
TP391.4
文献标志码:
A
摘要:
立体匹配有着广泛的应用前景，是计算机视觉领域的研究热点。立体匹配是立体视觉中最为关键和困难的一步，它的目标是计算标识匹配像素位置的视差图。文中提出的立体匹配算法基于置信传播（Belief Propagation，BP）。左图像首先经过非均匀采样，得到一个内容自适应的网格近似表示。算法的关键是使用基于置信传播的立体匹配算法，匹配稀疏的左图像和右图像得到稀疏视差图。通过左图像得到网格，稀疏视差图可以经过简单的插值得到稠密视差图。实验结果表明，该方法与现有稀疏立体匹配技术相比在视差图质量上平均有40％的提高
Abstract:
Stereo matching with a wide range of applications is an important research field in computer vision. Stereo matching is also the key and the most difficult problem in stereo vision, its objective is to calculate the disparity map of identified pixel. The proposed stereo matching algorithm is based on belief propagation （BP）. Firstly, a content adaptive mesh is obtained by the non-uniform sampling of the left image. The key issue in the proposed method is to formulate BP, matching the sparse left image and dense right images to get sparse disparity map. We can recover the dense depth map form sparse one due to a simple proposed interpolation method that benefits from the mesh approximation of the left image. The results obtained show that the sparse stereo matching with the existing technology in the quality of depth maps had an average 40% improvement

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备注/Memo

备注/Memo:
中国民用航空局科研项目（MHRD200924）陈佳坤（1985-），男，硕士生，研究方向为计算机算法、图像处理与计算机视觉；罗谦，博士研究生，研究方向为数据挖掘、进化计算、企业智能计算
更新日期/Last Update: 1900-01-01