{"title":"视觉Beltrami框架中的仿射不变性","authors":"N. Sochen","doi":"10.1109/VLSM.2001.938881","DOIUrl":null,"url":null,"abstract":"We use the geometric Beltrami framework to incorporate and explain some of the known invariant flows, e.g., the equi-affine invariant flow. It is also demonstrated that the new concepts put forward in this framework enable us to construct new invariant flows for the case where the codimension is greater than one, e.g., for color images and video.","PeriodicalId":445975,"journal":{"name":"Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"On affine invariance in the Beltrami framework for vision\",\"authors\":\"N. Sochen\",\"doi\":\"10.1109/VLSM.2001.938881\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We use the geometric Beltrami framework to incorporate and explain some of the known invariant flows, e.g., the equi-affine invariant flow. It is also demonstrated that the new concepts put forward in this framework enable us to construct new invariant flows for the case where the codimension is greater than one, e.g., for color images and video.\",\"PeriodicalId\":445975,\"journal\":{\"name\":\"Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VLSM.2001.938881\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSM.2001.938881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On affine invariance in the Beltrami framework for vision
We use the geometric Beltrami framework to incorporate and explain some of the known invariant flows, e.g., the equi-affine invariant flow. It is also demonstrated that the new concepts put forward in this framework enable us to construct new invariant flows for the case where the codimension is greater than one, e.g., for color images and video.