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发表刊物：Computer-Aided Design
关键字：Surface reconstructionContinuous global optimizationConvex relaxation
摘要：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
论文类型：期刊论文
学科门类：工学
一级学科：软件工程
文献类型：J
卷号：43
期号：8
字数：6000
是否译文：否
发表时间：2011-08-01
收录刊物：SCI