Competing Fronts for Coarse-to-Fine Surface Reconstruction

Andrei Sharf, Thomas Lewiner, Ariel Shamir, Leif Kobbelt, Daniel Cohen-Or

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

Abstract

We present a deformable model to reconstruct a surface from a point cloud. The model is bused on an explicit mesh representation composed of multiple competing evolving fronts. These fronts adapt to the local feature size of the target shape in a coarse-to-fine manner. Hence, they approach towards the finer (local) features of the target shape only after the reconstruction of the coarse (global) features has been completed. This conservative approach leads to a better control and interpretation of the reconstructed topology. The use of an explicit representation for the deformable model guarantees water-tightness and simple tracking of topological events. Furthermore, the coarse-to-fine nature of reconstruction enables adaptive handling of non-homogenous sample density, including robustness to missing data in defected areas.

Original languageEnglish
Pages (from-to)389-398
Number of pages10
JournalComputer Graphics Forum
Volume25
Issue number3
DOIs
StatePublished - 2006
Externally publishedYes

Keywords

  • Deformable models
  • Surface reconstruction

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

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