Shape Representation and Image Segmentation Using Deformable Surfaces

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
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Communication dans un congrès
International Conference on Computer Vision & Pattern Recognition (CVPR '91), Jun 1991, Maui, Hawai, United States. IEEE, pp.467-472, 1991, 〈10.1109/CVPR.1991.139737〉
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Hervé Delingette, Martial Hébert, Katsuchi Ikeuchi. Shape Representation and Image Segmentation Using Deformable Surfaces. International Conference on Computer Vision & Pattern Recognition (CVPR '91), Jun 1991, Maui, Hawai, United States. IEEE, pp.467-472, 1991, 〈10.1109/CVPR.1991.139737〉. 〈inria-00615554〉

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