{"title":"Perceptually based approach for planar shape morphing","authors":"Ligang Liu, Guopu Wang, Bo Zhang, B. Guo, H. Shum","doi":"10.1109/PCCGA.2004.1348341","DOIUrl":null,"url":null,"abstract":"This paper presents an approach for establishing vertex correspondences between two planar shapes. Correspondences are established between the perceptual feature points extracted from both source and target shapes. A similarity metric between two feature points is defined using the intrinsic properties of their local neighborhoods. The optimal correspondence is found by an efficient dynamic programming technique. Our approach treats shape noise by allowing discarding small feature points, which introduces skips in the traversal of the dynamic programming graph. Our method is fast, feature preserving, and invariant to geometric transformations. We demonstrate the superiority of our approach over other approaches by experimental results.","PeriodicalId":264796,"journal":{"name":"12th Pacific Conference on Computer Graphics and Applications, 2004. PG 2004. Proceedings.","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"55","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"12th Pacific Conference on Computer Graphics and Applications, 2004. PG 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCCGA.2004.1348341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 55
Abstract
This paper presents an approach for establishing vertex correspondences between two planar shapes. Correspondences are established between the perceptual feature points extracted from both source and target shapes. A similarity metric between two feature points is defined using the intrinsic properties of their local neighborhoods. The optimal correspondence is found by an efficient dynamic programming technique. Our approach treats shape noise by allowing discarding small feature points, which introduces skips in the traversal of the dynamic programming graph. Our method is fast, feature preserving, and invariant to geometric transformations. We demonstrate the superiority of our approach over other approaches by experimental results.