Shape Modeling and Applications, International Conference on (2006)
June 14, 2006 to June 16, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SMI.2006.38
Shin Yoshizawa , MPI Informatik, Germany
Alexander Belyaev , MPI Informatik, Germany
Hans-Peter Seidel , MPI Informatik, Germany
In this paper, we propose a new and powerful shape denoising technique for processing surfaces approximated by triangle meshes and soups. Our approach is inspired by recent non-local image denoising schemes and naturally extends bilateral mesh smoothing methods. The main idea behind the approach is very simple. A new position of vertex P of a noisy mesh is obtained as a weighted mean of mesh vertices Q with nonlinear weights reflecting a similarity between local neighborhoods of P and Q. We demonstrate that our technique outperforms recent state-of-the-art smoothing methods. We also suggest a new scheme for comparing different mesh/soup denoising methods.
S. Yoshizawa, A. Belyaev and H. Seidel, "Smoothing by Example: Mesh Denoising by Averaging with Similarity-Based Weights," IEEE International Conference on Shape Modeling and Applications 2006(SMI), Matsushima, 2006, pp. 9.