{"title":"基于距离图像的三维地标识别","authors":"M. Herbert","doi":"10.1109/CVPR.1992.223164","DOIUrl":null,"url":null,"abstract":"Progress in building and recognizing models of objects for an autonomous vehicle for on-road and cross-country navigation is reported. The object models are stored in a map and are used as landmarks for estimating vehicle position. The landmarks can be used as intermediate control points at which the vehicle must take some prescribed action in the case of a complex mission. Robust object tracking using sequences of range images and building and updating 3-D object representations is presented. Tracking uses object prediction from one image to the next to accurately compute object locations. Object representations are built by merging sets of points from individual images into a single set in an object-centered coordinate frame. The sparse set of points is then segmented into shapes yielding compact and general object representations. An algorithm for landmark identification in range images is introduced in the context of map-based navigation.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"3-D landmark recognition from range images\",\"authors\":\"M. Herbert\",\"doi\":\"10.1109/CVPR.1992.223164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Progress in building and recognizing models of objects for an autonomous vehicle for on-road and cross-country navigation is reported. The object models are stored in a map and are used as landmarks for estimating vehicle position. The landmarks can be used as intermediate control points at which the vehicle must take some prescribed action in the case of a complex mission. Robust object tracking using sequences of range images and building and updating 3-D object representations is presented. Tracking uses object prediction from one image to the next to accurately compute object locations. Object representations are built by merging sets of points from individual images into a single set in an object-centered coordinate frame. The sparse set of points is then segmented into shapes yielding compact and general object representations. An algorithm for landmark identification in range images is introduced in the context of map-based navigation.<<ETX>>\",\"PeriodicalId\":325476,\"journal\":{\"name\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"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.1992.223164\",\"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.1992.223164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Progress in building and recognizing models of objects for an autonomous vehicle for on-road and cross-country navigation is reported. The object models are stored in a map and are used as landmarks for estimating vehicle position. The landmarks can be used as intermediate control points at which the vehicle must take some prescribed action in the case of a complex mission. Robust object tracking using sequences of range images and building and updating 3-D object representations is presented. Tracking uses object prediction from one image to the next to accurately compute object locations. Object representations are built by merging sets of points from individual images into a single set in an object-centered coordinate frame. The sparse set of points is then segmented into shapes yielding compact and general object representations. An algorithm for landmark identification in range images is introduced in the context of map-based navigation.<>