{"title":"关于立体几何约束的推导","authors":"C. Stewart","doi":"10.1109/CVPR.1992.223177","DOIUrl":null,"url":null,"abstract":"Probability density functions (PDFs) are derived for many of the geometric measurements upon which stereo matching techniques are based, including orientation differences between matching line segments or curves, the gradient of disparity, the directional derivative of disparity, and disparity differences between matches. The PDFs resulting from the transformations are used to critically examine many existing stereo techniques. Several techniques based on these PDFs are proposed.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"On the derivation of geometric constraints in stereo\",\"authors\":\"C. Stewart\",\"doi\":\"10.1109/CVPR.1992.223177\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Probability density functions (PDFs) are derived for many of the geometric measurements upon which stereo matching techniques are based, including orientation differences between matching line segments or curves, the gradient of disparity, the directional derivative of disparity, and disparity differences between matches. The PDFs resulting from the transformations are used to critically examine many existing stereo techniques. Several techniques based on these PDFs are proposed.<<ETX>>\",\"PeriodicalId\":325476,\"journal\":{\"name\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.1992.223177\",\"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 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1992.223177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the derivation of geometric constraints in stereo
Probability density functions (PDFs) are derived for many of the geometric measurements upon which stereo matching techniques are based, including orientation differences between matching line segments or curves, the gradient of disparity, the directional derivative of disparity, and disparity differences between matches. The PDFs resulting from the transformations are used to critically examine many existing stereo techniques. Several techniques based on these PDFs are proposed.<>