W. Niessen, J. Duncan, L. Florack, B. M. terHaarRomeny, M. Viergever
{"title":"时空算子和光流","authors":"W. Niessen, J. Duncan, L. Florack, B. M. terHaarRomeny, M. Viergever","doi":"10.1109/PBMCV.1995.514671","DOIUrl":null,"url":null,"abstract":"This paper describes efforts to extract motion characteristics of\na scene directly from the gray-scale data. The measurements are, by the\nvery nature of the sampling of image data, integral values. The approach\nsolves the ill-posedness of differentiation. A complete class of\nspatiotemporal operators which concisely captures the local\nspatiotemporal information tip to any order in space and time is\nproposed. Spatial and temporal scale are treated as free parameters. The\noperators are used to extract spatiotemporal features and to estimate\nthe velocity field. In the estimation of the velocity field we use the\ngeneralized optic flow constraint equation, in which the signal over a\nregion which may be subject to the flow field is conserved rather than\nthe gray-value associated with a voxel. Examples on test images and\nMR-data of the Left Ventricle are shown","PeriodicalId":343932,"journal":{"name":"Proceedings of the Workshop on Physics-Based Modeling in Computer Vision","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Spatiotemporal operators and optic flow\",\"authors\":\"W. Niessen, J. Duncan, L. Florack, B. M. terHaarRomeny, M. Viergever\",\"doi\":\"10.1109/PBMCV.1995.514671\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes efforts to extract motion characteristics of\\na scene directly from the gray-scale data. The measurements are, by the\\nvery nature of the sampling of image data, integral values. The approach\\nsolves the ill-posedness of differentiation. A complete class of\\nspatiotemporal operators which concisely captures the local\\nspatiotemporal information tip to any order in space and time is\\nproposed. Spatial and temporal scale are treated as free parameters. The\\noperators are used to extract spatiotemporal features and to estimate\\nthe velocity field. In the estimation of the velocity field we use the\\ngeneralized optic flow constraint equation, in which the signal over a\\nregion which may be subject to the flow field is conserved rather than\\nthe gray-value associated with a voxel. Examples on test images and\\nMR-data of the Left Ventricle are shown\",\"PeriodicalId\":343932,\"journal\":{\"name\":\"Proceedings of the Workshop on Physics-Based Modeling in Computer Vision\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Workshop on Physics-Based Modeling in Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PBMCV.1995.514671\",\"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 of the Workshop on Physics-Based Modeling in Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PBMCV.1995.514671","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes efforts to extract motion characteristics of
a scene directly from the gray-scale data. The measurements are, by the
very nature of the sampling of image data, integral values. The approach
solves the ill-posedness of differentiation. A complete class of
spatiotemporal operators which concisely captures the local
spatiotemporal information tip to any order in space and time is
proposed. Spatial and temporal scale are treated as free parameters. The
operators are used to extract spatiotemporal features and to estimate
the velocity field. In the estimation of the velocity field we use the
generalized optic flow constraint equation, in which the signal over a
region which may be subject to the flow field is conserved rather than
the gray-value associated with a voxel. Examples on test images and
MR-data of the Left Ventricle are shown