47
Views
0
CrossRef citations to date
0
Altmetric
Original Article

Globally optimal estimate for variational surface reconstruction

, &
Pages 97-102 | Accepted 24 Feb 2011, Published online: 12 Nov 2013
 

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.

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).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 305.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.