{"title":"一种基于混合内禀映射的密集对应算法","authors":"Dan Kang, Xiuyang Zhao, Zhiang Chen, Mingjun Liu","doi":"10.1109/CISP.2015.7407932","DOIUrl":null,"url":null,"abstract":"The dense matching of 3-D meshes is an important research topic in the field of computer vision. In this paper, we present a layered matching pipeline based on the mixed corresponding grid dense matching algorithm. Firstly, this algorithm find an intrinsic map between two non-isometric, genus zero surfaces. Secondly, we use the nature of the bottom of the measure preserving distance to released the dense corresponding of surfaces. A set of experimental results show that the proposed method achieves better approximation accuracy than the ICP method.","PeriodicalId":167631,"journal":{"name":"2015 8th International Congress on Image and Signal Processing (CISP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An algorithm for dense correspondence based on blended intrinsic map\",\"authors\":\"Dan Kang, Xiuyang Zhao, Zhiang Chen, Mingjun Liu\",\"doi\":\"10.1109/CISP.2015.7407932\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The dense matching of 3-D meshes is an important research topic in the field of computer vision. In this paper, we present a layered matching pipeline based on the mixed corresponding grid dense matching algorithm. Firstly, this algorithm find an intrinsic map between two non-isometric, genus zero surfaces. Secondly, we use the nature of the bottom of the measure preserving distance to released the dense corresponding of surfaces. A set of experimental results show that the proposed method achieves better approximation accuracy than the ICP method.\",\"PeriodicalId\":167631,\"journal\":{\"name\":\"2015 8th International Congress on Image and Signal Processing (CISP)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 8th International Congress on Image and Signal Processing (CISP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP.2015.7407932\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 8th International Congress on Image and Signal Processing (CISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2015.7407932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An algorithm for dense correspondence based on blended intrinsic map
The dense matching of 3-D meshes is an important research topic in the field of computer vision. In this paper, we present a layered matching pipeline based on the mixed corresponding grid dense matching algorithm. Firstly, this algorithm find an intrinsic map between two non-isometric, genus zero surfaces. Secondly, we use the nature of the bottom of the measure preserving distance to released the dense corresponding of surfaces. A set of experimental results show that the proposed method achieves better approximation accuracy than the ICP method.