Title :
3-D landmark recognition from range images
Author_Institution :
Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA
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
Keywords :
image recognition; surface fitting; 3-D object representations; 3D landmark recognition; autonomous vehicle; cross-country navigation; landmark identification; landmark recognition; map-based navigation; object models; object tracking; object-centered coordinate frame; range images; vehicle position; Contracts; Image recognition; Image segmentation; Merging; Mobile robots; Navigation; Remotely operated vehicles; Robot kinematics; Robustness; Shape;
Conference_Titel :
Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
Conference_Location :
Champaign, IL
Print_ISBN :
0-8186-2855-3
DOI :
10.1109/CVPR.1992.223164