DocumentCode :
2643218
Title :
Geometric and photometric constraints for surface recovery
Author :
Lu, Jiping ; Little, Jim
Author_Institution :
Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC, Canada
fYear :
1996
fDate :
18-20 Jun 1996
Firstpage :
694
Lastpage :
700
Abstract :
In this paper we present a novel approach to surface recovery from an image sequence of a rotating object. In this approach, the object is illuminated under a collinear light source (where the light source lies on or near the optical axis) and rotated on a controlled turntable. A wire-frame of 3D curves on the object surface is extracted by using shading and occluding contours in the image sequence. Then the whole object surface is recovered by interpolating the surface between curves on the wire-frame. The interpolation can be done by using geometric or photometric constraints. The photometric method uses shading information and is more powerful than geometric methods. The experimental results on real image sequence of matte and specular surfaces show that the technique is feasible and promising
Keywords :
computer vision; image sequences; interpolation; 3D curves; collinear light source; controlled turntable; geometric constraints; image sequence; interpolation; object surface; occluding contours; optical axis; photometric constraints; photometric method; rotating object; shading; shading information; surface recovery; Cameras; Computational intelligence; Data mining; Image sequences; Laboratories; Light sources; Photometry; Reflectivity; Shape; Stereo vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on
Conference_Location :
San Francisco, CA
ISSN :
1063-6919
Print_ISBN :
0-8186-7259-5
Type :
conf
DOI :
10.1109/CVPR.1996.517148
Filename :
517148
Link To Document :
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