Title :
Recovering and tracking pose of curved 3D objects from 2D images
Author :
Chen, Jin-Long ; Stockman, George C. ; Rao, Kashi
Author_Institution :
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
Abstract :
A method of locating and tracking rigid moving objects with arbitrary curved surfaces is presented. Motion of the moving objects in a sequence of images is used to perform image segmentation and boundary extraction. The silhouette of the object model is derived by the curvature method of Basri and Ullman. The derived silhouette is then fitted to the observed silhouette to determine the object pose. Correspondence is guided by template matching, where the similarity measure is based on the minimization of the overall Euclidean distance between the derived silhouette and the observed silhouette. Bench tests and simulations confirm the viability of the approach, even when the observed silhouette is imperfect due to partial occlusion of the object or imperfect boundary extraction
Keywords :
image recognition; image restoration; image segmentation; image sequences; object recognition; 2D images; Euclidean distance; boundary extraction; curvature method; curved 3D objects; curved surfaces; image segmentation; image sequence; object model; pose recovering; pose tracking; rigid moving objects; silhouette; template matching; Computer science; Euclidean distance; Feature extraction; Image segmentation; Layout; Machine vision; Object recognition; Rough surfaces; Surface roughness; Testing;
Conference_Titel :
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-3880-X
DOI :
10.1109/CVPR.1993.340984
