{"title":"隐曲面曲率的可靠估计","authors":"Jacob D. Hauenstein, Timothy S Newman","doi":"10.1109/3DV.2014.30","DOIUrl":null,"url":null,"abstract":"Estimation of curvature in volumetric datasets is considered. One component of the exhibition here is new extensions of several known methods for such estimations in range images to the new domain of volumetric datasets. A second component is that the (1) accuracy and (2) computational performance of these extensions (and five well-known existing methods for curvature estimation in volumetric datasets) are comparatively examined.","PeriodicalId":275516,"journal":{"name":"2014 2nd International Conference on 3D Vision","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"On Reliable Estimation of Curvatures of Implicit Surfaces\",\"authors\":\"Jacob D. Hauenstein, Timothy S Newman\",\"doi\":\"10.1109/3DV.2014.30\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Estimation of curvature in volumetric datasets is considered. One component of the exhibition here is new extensions of several known methods for such estimations in range images to the new domain of volumetric datasets. A second component is that the (1) accuracy and (2) computational performance of these extensions (and five well-known existing methods for curvature estimation in volumetric datasets) are comparatively examined.\",\"PeriodicalId\":275516,\"journal\":{\"name\":\"2014 2nd International Conference on 3D Vision\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 2nd International Conference on 3D Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/3DV.2014.30\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 2nd International Conference on 3D Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3DV.2014.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On Reliable Estimation of Curvatures of Implicit Surfaces
Estimation of curvature in volumetric datasets is considered. One component of the exhibition here is new extensions of several known methods for such estimations in range images to the new domain of volumetric datasets. A second component is that the (1) accuracy and (2) computational performance of these extensions (and five well-known existing methods for curvature estimation in volumetric datasets) are comparatively examined.