Journal:Computer-Aided Design
Key Words:Surface reconstructionContinuous global optimizationConvex relaxation
Abstract:We introduce a continuous global optimization method to the field of surface reconstruction from discrete noisy cloud of points with weak information on orientation. The proposed method uses an energy functional combining flux-based data-fit measures and a regularization term. A continuous convex relaxation scheme assures the global minima of the geometric surface functional. The reconstructed surface is implicitly represented by the binary segmentation of vertices of a 3D uniform grid and a triangulated surface can be obtained by extracting an appropriate isosurface. Unlike the discrete graph
Indexed by:Journal paper
Discipline:Engineering
First-Level Discipline:Software Engineering
Document Type:J
Volume:43
Issue:8
Number of Words:6000
Translation or Not:no
Date of Publication:2011-08-01
Included Journals:SCI
Date of Publication:2011-08-01