{"title":"Affine trackability aids obstacle detection","authors":"H. Sawhney, A. Hanson","doi":"10.1109/CVPR.1992.223156","DOIUrl":null,"url":null,"abstract":"Potential obstacles in the path of a mobile robot that can often be characterized as shallow (i.e., their extent in depth is small compared to their distance from the camera) are considered. The constraint of affine trackability is applied to automatic identification and 3-D reconstruction of shallow structures in realistic scenes. It is shown how this approach can handle independent object motion, occlusion, and motion discontinuity. Although the reconstructed structure is only a frontal plane approximation to the corresponding real structure, the robustness of depth of the approximation might be useful for obstacle avoidance, where the exact shape of an object may not be of consequence so long as collisions with it can be avoided.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","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.1992.223156","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Potential obstacles in the path of a mobile robot that can often be characterized as shallow (i.e., their extent in depth is small compared to their distance from the camera) are considered. The constraint of affine trackability is applied to automatic identification and 3-D reconstruction of shallow structures in realistic scenes. It is shown how this approach can handle independent object motion, occlusion, and motion discontinuity. Although the reconstructed structure is only a frontal plane approximation to the corresponding real structure, the robustness of depth of the approximation might be useful for obstacle avoidance, where the exact shape of an object may not be of consequence so long as collisions with it can be avoided.<>