Non-Iterative, Feature-Preserving Mesh Smoothing
Author(s)
Jones, Thouis R.
Durand, Frédo
Desbrun, Mathieu
Date Issued
January 2004
Series/Report no.
Computer Science (CS);
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.
Subjects
mesh smoothing
robust statistics
mollification
feature preservation
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