{"title":"A shape-based stereo matching algorithm for binocular vision","authors":"Xinjian Fan, Xuelin Wang, Yongfei Xiao","doi":"10.1109/SPAC.2014.6982659","DOIUrl":null,"url":null,"abstract":"Binocular stereo vision is an important branch of the research area in computer vision. Stereo matching is the most important process in binocular vision. In this paper, a new stereo matching scheme using shape-based matching (SBM) is presented to improve the depth reconstruction method of binocular stereo vision systems. The method works in two steps. First, an operator registers the pattern including the key features of an object to be measured. Then during the operation stage, the stereo camera snaps stereo images and finds the patterns in right and left images separately by means of the SBM. The 3D positions of the object are calculated by using the corresponding points of the stereo images and the projection matrices of the stereo camera. Since we apply robust image processing algorithms, such as the SBM, the proposed method becomes more reliable than the conventional stereo vision systems.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAC.2014.6982659","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Binocular stereo vision is an important branch of the research area in computer vision. Stereo matching is the most important process in binocular vision. In this paper, a new stereo matching scheme using shape-based matching (SBM) is presented to improve the depth reconstruction method of binocular stereo vision systems. The method works in two steps. First, an operator registers the pattern including the key features of an object to be measured. Then during the operation stage, the stereo camera snaps stereo images and finds the patterns in right and left images separately by means of the SBM. The 3D positions of the object are calculated by using the corresponding points of the stereo images and the projection matrices of the stereo camera. Since we apply robust image processing algorithms, such as the SBM, the proposed method becomes more reliable than the conventional stereo vision systems.