{"title":"基于人脸特征区域划分的网格简化","authors":"An-Bing Wang, Bin Yu, Zhi-Jing Liu","doi":"10.1109/IASP.2009.5054636","DOIUrl":null,"url":null,"abstract":"This paper proposes a mesh simplification method based on facial features region partition for the special three-dimensional facial mesh model. According to distribution of feature points, the face is divided into several parts consisting of critical feature regional and non-critical feature regional. This method adjusts different areas using different curvature values. This algorithm also uses edge collapse method to reduce the density of meshes. As curvature is useful to enhance the shape description, the high details of key feature area are kept while other areas are simplified.","PeriodicalId":143959,"journal":{"name":"2009 International Conference on Image Analysis and Signal Processing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Mesh simplification based on facial features region partition\",\"authors\":\"An-Bing Wang, Bin Yu, Zhi-Jing Liu\",\"doi\":\"10.1109/IASP.2009.5054636\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a mesh simplification method based on facial features region partition for the special three-dimensional facial mesh model. According to distribution of feature points, the face is divided into several parts consisting of critical feature regional and non-critical feature regional. This method adjusts different areas using different curvature values. This algorithm also uses edge collapse method to reduce the density of meshes. As curvature is useful to enhance the shape description, the high details of key feature area are kept while other areas are simplified.\",\"PeriodicalId\":143959,\"journal\":{\"name\":\"2009 International Conference on Image Analysis and Signal Processing\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Image Analysis and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IASP.2009.5054636\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Image Analysis and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IASP.2009.5054636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mesh simplification based on facial features region partition
This paper proposes a mesh simplification method based on facial features region partition for the special three-dimensional facial mesh model. According to distribution of feature points, the face is divided into several parts consisting of critical feature regional and non-critical feature regional. This method adjusts different areas using different curvature values. This algorithm also uses edge collapse method to reduce the density of meshes. As curvature is useful to enhance the shape description, the high details of key feature area are kept while other areas are simplified.