Minimal Surfaces Based Object Segmentation

Authors:
Vincent Caselles;Ron Kimmel;Guillermo Sapiro;Catalina Sbert
Affiliations:
-;-;-;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1997

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Abstract

A geometric approach for 3D object segmentation and representation is presented. The segmentation is obtained by deformable surfaces moving towards the objects to be detected in the 3D image. The model is based on curvature motion and the computation of surfaces with minimal areas, better known as minimal surfaces. The space where the surfaces are computed is induced from the 3D image (volumetric data) in which the objects are to be detected. The model links between classical deformable surfaces obtained via energy minimization, and intrinsic ones derived from curvature based flows. The new approach is stable, robust, and automatically handles changes in the surface topology during the deformation.