{"title":"从双目图像流中恢复三维平移运动并建立立体对应关系","authors":"L. Li, J. Duncan","doi":"10.1109/WVM.1989.47126","DOIUrl":null,"url":null,"abstract":"Stereo imagery with translational motion is analyzed. It is shown that the relative translational velocity between the camera platform and the objects can be computed by solving linear equations based on the measured flow fields of the left and right cameras, without point-to-point correspondence. In addition, stereo matching procedures based on the estimate translational velocity and the flow fields are presented. Preliminary results with synthetic data show that these techniques are quite robust in the presence of noise.<<ETX>>","PeriodicalId":342419,"journal":{"name":"[1989] Proceedings. Workshop on Visual Motion","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Recovering 3-D translational motion and establishing stereo correspondence from binocular image flows\",\"authors\":\"L. Li, J. Duncan\",\"doi\":\"10.1109/WVM.1989.47126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stereo imagery with translational motion is analyzed. It is shown that the relative translational velocity between the camera platform and the objects can be computed by solving linear equations based on the measured flow fields of the left and right cameras, without point-to-point correspondence. In addition, stereo matching procedures based on the estimate translational velocity and the flow fields are presented. Preliminary results with synthetic data show that these techniques are quite robust in the presence of noise.<<ETX>>\",\"PeriodicalId\":342419,\"journal\":{\"name\":\"[1989] Proceedings. Workshop on Visual Motion\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1989] Proceedings. Workshop on Visual Motion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WVM.1989.47126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1989] Proceedings. Workshop on Visual Motion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WVM.1989.47126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recovering 3-D translational motion and establishing stereo correspondence from binocular image flows
Stereo imagery with translational motion is analyzed. It is shown that the relative translational velocity between the camera platform and the objects can be computed by solving linear equations based on the measured flow fields of the left and right cameras, without point-to-point correspondence. In addition, stereo matching procedures based on the estimate translational velocity and the flow fields are presented. Preliminary results with synthetic data show that these techniques are quite robust in the presence of noise.<>