{"title":"Efficient partial shape matching using Smith-Waterman algorithm","authors":"Longbin Chen, R. Feris, M. Turk","doi":"10.1109/CVPRW.2008.4563078","DOIUrl":null,"url":null,"abstract":"This paper presents an efficient partial shape matching method based on the Smith-Waterman algorithm. For two contours of m and n points respectively, the complexity of our method to find similar parts is only O(mn). In addition to this improvement in efficiency, we also obtain comparable accurate matching with fewer shape descriptors. Also, in contrast to arbitrary distance functions that are used by previous methods, we use a probabilistic similarity measurement, p-value, to evaluate the similarity of two shapes. Our experiments on several public shape databases indicate that our method outperforms state-of-the-art global and partial shape matching algorithms in various scenarios.","PeriodicalId":102206,"journal":{"name":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"76","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2008.4563078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 76
Abstract
This paper presents an efficient partial shape matching method based on the Smith-Waterman algorithm. For two contours of m and n points respectively, the complexity of our method to find similar parts is only O(mn). In addition to this improvement in efficiency, we also obtain comparable accurate matching with fewer shape descriptors. Also, in contrast to arbitrary distance functions that are used by previous methods, we use a probabilistic similarity measurement, p-value, to evaluate the similarity of two shapes. Our experiments on several public shape databases indicate that our method outperforms state-of-the-art global and partial shape matching algorithms in various scenarios.