A new vector field distance transform and its application to mesh processing from 3D scanned data

  • Authors:
  • Marc Fournier;Jean-Michel Dischler;Dominique Bechmann

  • Affiliations:
  • LSIIT – UMR 7005 – CNRS – Louis Pasteur University, Image Sciences, Computer Sciences and Remote Sensing Laboratory, 4 rue Blaise Pascal, 67070, Strasbourg, France;LSIIT – UMR 7005 – CNRS – Louis Pasteur University, Image Sciences, Computer Sciences and Remote Sensing Laboratory, 4 rue Blaise Pascal, 67070, Strasbourg, France;LSIIT – UMR 7005 – CNRS – Louis Pasteur University, Image Sciences, Computer Sciences and Remote Sensing Laboratory, 4 rue Blaise Pascal, 67070, Strasbourg, France

  • Venue:
  • The Visual Computer: International Journal of Computer Graphics
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we define a new 3D vector field distance transform to implicitly represent a mesh surface. We show that this new representation is more accurate than the classic scalar field distance transform by comparing both representations with an error metric evaluation. The widely used marching cube triangulation algorithm is adapted to the new vector field distance transform to correctly reconstruct the resulting explicit surface. In the reconstruction process of 3D scanned data, the useful mesh denoising operation is extended to the new vector field representation, which enables adaptive and selective filtering features. Results show that mesh processing with this new vector field representation is more accurate than with the scalar field distance transform and that it outperforms previous mesh filtering algorithms. Future work is discussed to extend this new vector field representation to other mesh useful operations and applications.