Non-iterative, feature-preserving mesh smoothing

  • Authors:
  • Thouis R. Jones;Frédo Durand;Mathieu Desbrun

  • Affiliations:
  • MIT;MIT;USC

  • Venue:
  • ACM SIGGRAPH 2003 Papers
  • Year:
  • 2003

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Abstract

With the increasing use of geometry scanners to create 3D models, there is a rising need for fast and robust mesh smoothing to remove inevitable noise in the measurements. While most previous work has favored diffusion-based iterative techniques for feature-preserving smoothing, we propose a radically different approach, based on robust statistics and local first-order predictors of the surface. The robustness of our local estimates allows us to derive a non-iterative feature-preserving filtering technique applicable to arbitrary "triangle soups". We demonstrate its simplicity of implementation and its efficiency, which make it an excellent solution for smoothing large, noisy, and non-manifold meshes.