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

fYear

1993

fDate

15-17 Jun 1993

Firstpage

233

Lastpage

239

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on

Conference_Location

New York, NY

ISSN

1063-6919

Print_ISBN

0-8186-3880-X

Type

conf

DOI

10.1109/CVPR.1993.340984

Filename

340984