{"title":"Deformable geometry model matching by topological and geometric signatures","authors":"G. Tam, Rynson W. H. Lau, C. Ngo","doi":"10.1109/ICPR.2004.1334676","DOIUrl":null,"url":null,"abstract":"In this paper, we present a novel method for efficient 3D model comparison. The method matches highly deformed models by comparing topological and geometric features. First, we propose \"bi-directional LSD analysis\" to locate reliable topological points and rings. Second, based on these points and rings, sets of bounded regions are extracted as topological features. Third, for each bounded region, we capture additional spatial location, curvature and area distribution as geometric data. Fourth, to model the topological importance of each bounded region, we capture its effective area as weight. By using \"earth mover distance\" as a distance measure between two models, our method can achieve a high accuracy in our retrieval experiment, with precision of 0.53 even at recall rate of 1.0.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2004.1334676","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, we present a novel method for efficient 3D model comparison. The method matches highly deformed models by comparing topological and geometric features. First, we propose "bi-directional LSD analysis" to locate reliable topological points and rings. Second, based on these points and rings, sets of bounded regions are extracted as topological features. Third, for each bounded region, we capture additional spatial location, curvature and area distribution as geometric data. Fourth, to model the topological importance of each bounded region, we capture its effective area as weight. By using "earth mover distance" as a distance measure between two models, our method can achieve a high accuracy in our retrieval experiment, with precision of 0.53 even at recall rate of 1.0.