{"title":"Incorporating differential constraints in a 3D reconstruction process application to stereo","authors":"R. Lengagne, P. Fua","doi":"10.1109/ICCV.2001.937569","DOIUrl":null,"url":null,"abstract":"We propose to incorporate a priori geometric constraints in a 3-D stereo reconstruction scheme to cope with the many cases where image information alone is not sufficient to accurately recover 3-D shape. Our approach is based on the iterative deformation of a 3-D surface mesh to minimize an objective function. We show that combining anisotropic meshing with a nonquadratic approach to regularization enables us to obtain satisfactory reconstruction results using triangulations with few vertices. Structural or numerical constraints can then be added locally to the reconstruction process through a constrained optimization scheme. They improve the reconstruction results and enforce their consistency with a priori knowledge about object shape. The strong description and modeling properties of differential features make them useful tools that can be efficiently used as constraints for 3-D reconstruction.","PeriodicalId":429441,"journal":{"name":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2001.937569","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
We propose to incorporate a priori geometric constraints in a 3-D stereo reconstruction scheme to cope with the many cases where image information alone is not sufficient to accurately recover 3-D shape. Our approach is based on the iterative deformation of a 3-D surface mesh to minimize an objective function. We show that combining anisotropic meshing with a nonquadratic approach to regularization enables us to obtain satisfactory reconstruction results using triangulations with few vertices. Structural or numerical constraints can then be added locally to the reconstruction process through a constrained optimization scheme. They improve the reconstruction results and enforce their consistency with a priori knowledge about object shape. The strong description and modeling properties of differential features make them useful tools that can be efficiently used as constraints for 3-D reconstruction.