Globally optimal estimate for variational surface reconstruction

Abstract

In this article, we tackle the problem of using globally optimal estimate for variational surface reconstruction. We give an overview of globally optimal method on variational surface when the three-dimensional (3D) surface is represented by a point-based surface and a triangular mesh-based surface, and we detail the variational surface used on surface reconstruction. It can be applied to derive a range of meaningful surface reconstructions from this high dimensional space. We show that using a progression of spatially varying anisotropic weights can achieve significant improvements in surface reconstruction. Simulated surfaces and real model are experimentally studied, and the results validate that the proposed approaches improved the reconstruction. The proposed method improved the reconstruction results significantly for the simulated and real data.

Keywords:

• globally optimal estimate
• variational surface reconstruction
• point cloud

This research work is supported by the National Natural Science Foundation of China (nos. 60873130 and 60872115), the Shanghai’s Key Discipline Development Program (no. J50104) and the Shanghai University’s Graduate Student Innovative Fund (no. SHUCX101089).