DocumentCode :
2611243
Title :
Shape representation and image segmentation using deformable surfaces
Author :
Delingette, H. ; Hebert, M. ; Ikeuchi, K.
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
1991
fDate :
3-6 Jun 1991
Firstpage :
467
Lastpage :
472
Abstract :
A technique for constructing shape representation from images using free-form deformable surfaces is presented. The authors model an object as a closed surface that is deformed subject to attractive fields generated by input data points and features. Features affect the global shape of the surface, while data points control its local shape. This approach is used to segment objects even in cluttered or unstructured environments. The algorithm is general in that it makes few assumptions on the type of features, the nature of the data, and the type of objects. Results for a wide range of applications are presented: reconstruction of smooth isolated objects such as human faces, reconstruction of structured objects such as polyhedra, and segmentation of complex scenes with mutually occluding objects. The algorithm has been successfully tested using data from different sensors including grey-coding range finders and video cameras, using one or several images
Keywords :
encoding; pattern recognition; picture processing; attractive fields; closed surface; deformable surfaces; features; global shape; grey-coding range finders; human faces; image segmentation; input data points; mutually occluding objects; polyhedra; shape representation; smooth isolated objects; structured objects; video cameras; Cameras; Deformable models; Face; Humans; Image reconstruction; Image segmentation; Image sensors; Layout; Shape control; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
Conference_Location :
Maui, HI
ISSN :
1063-6919
Print_ISBN :
0-8186-2148-6
Type :
conf
DOI :
10.1109/CVPR.1991.139737
Filename :
139737
Link To Document :
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