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
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