An improved seed growth method for accurate stereo matching in disparity space  

作　　者：陆培源 王建中 罗涛 

机构地区：[1]State Key Laboratory of Explosion Science and Technology,Beijing Institute of Technology

出　　处：《Journal of Beijing Institute of Technology》2012年第1期35-40,共6页北京理工大学学报（英文版）

基　　金：Supported by State Key Laboratory of Explosion Science and Techno logy Foundation(YBKT11-7)

摘　　要：Matching is a classical problem in stereo vision. To solve the matching problem that components cannot continue growing on the occlusions region and repetitive patterns, an improved seed growth method is proposed. The method obtains a set of interesting points defined as initial seeds from a rectified image. Through global optimization the seeds and their neighbors can be selected in- to a match table. Finally the components grow with the matching points and create a semi-dense map under the maximum similar subset according to the principle of the unique constraint. Experimental results show that the proposed method in the grown process can rectify some errors in matching. The semi-dense map has a good performance in the occlusions region and repetitive patterns. This algorithm is faster and more accurate than the traditional seed growing method.Matching is a classical problem in stereo vision. To solve the matching problem that components cannot continue growing on the occlusions region and repetitive patterns, an improved seed growth method is proposed. The method obtains a set of interesting points defined as initial seeds from a rectified image. Through global optimization the seeds and their neighbors can be selected in- to a match table. Finally the components grow with the matching points and create a semi-dense map under the maximum similar subset according to the principle of the unique constraint. Experimental results show that the proposed method in the grown process can rectify some errors in matching. The semi-dense map has a good performance in the occlusions region and repetitive patterns. This algorithm is faster and more accurate than the traditional seed growing method.

关 键 词：global optimization seed growth disparity map stereo matching 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]