{"title":"具有等距约束的基于窗口的范围流","authors":"Ting Yu, J. Lang","doi":"10.1109/CRV.2010.50","DOIUrl":null,"url":null,"abstract":"This paper proposes a simple window-based range flow method which uses isometry of the observed surface as its primary matching constraint. The method uses feature points as anchoring references of the surface deformation. Given a set of matched features no other intensity information is used and hence the method can tolerate intensity changes over time. The range-flow equation is only required for a final verification step making the method robust to poor quality range images. This allows us to use the popular Point Grey Research Bumblebee 2 stereo-head to acquire our range data. The approach is shown to work well on two example scenes which capture non-rigid isometric and general deformations. The paper also presents experiments demonstrating the stability of the geodesic approximation employed in the isometry-based matching when the 3D point clouds are sparse.","PeriodicalId":358821,"journal":{"name":"2010 Canadian Conference on Computer and Robot Vision","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Window-Based Range Flow with an Isometry Constraint\",\"authors\":\"Ting Yu, J. Lang\",\"doi\":\"10.1109/CRV.2010.50\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a simple window-based range flow method which uses isometry of the observed surface as its primary matching constraint. The method uses feature points as anchoring references of the surface deformation. Given a set of matched features no other intensity information is used and hence the method can tolerate intensity changes over time. The range-flow equation is only required for a final verification step making the method robust to poor quality range images. This allows us to use the popular Point Grey Research Bumblebee 2 stereo-head to acquire our range data. The approach is shown to work well on two example scenes which capture non-rigid isometric and general deformations. The paper also presents experiments demonstrating the stability of the geodesic approximation employed in the isometry-based matching when the 3D point clouds are sparse.\",\"PeriodicalId\":358821,\"journal\":{\"name\":\"2010 Canadian Conference on Computer and Robot Vision\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Canadian Conference on Computer and Robot Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRV.2010.50\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Canadian Conference on Computer and Robot Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2010.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Window-Based Range Flow with an Isometry Constraint
This paper proposes a simple window-based range flow method which uses isometry of the observed surface as its primary matching constraint. The method uses feature points as anchoring references of the surface deformation. Given a set of matched features no other intensity information is used and hence the method can tolerate intensity changes over time. The range-flow equation is only required for a final verification step making the method robust to poor quality range images. This allows us to use the popular Point Grey Research Bumblebee 2 stereo-head to acquire our range data. The approach is shown to work well on two example scenes which capture non-rigid isometric and general deformations. The paper also presents experiments demonstrating the stability of the geodesic approximation employed in the isometry-based matching when the 3D point clouds are sparse.