Random walks for mesh denoising

Sun, Xianfang ORCID: https://orcid.org/0000-0002-6114-0766, Rosin, Paul L. ORCID: https://orcid.org/0000-0002-4965-3884, Martin, Ralph Robert and Langbein, Frank Curd ORCID: https://orcid.org/0000-0002-3379-0323 2007. Random walks for mesh denoising. Presented at: SPM 2007: ACM Symposium on Solid and Physical Modeling, Beijing, China, 4-6 June 2007. Proceedings, SPM 2007 : ACM Symposium on Solid and Physical Modeling : Beijing, China, June 04-06, 2007. New York, USA: Association for Computing Machinery, pp. 11-22. 10.1145/1236246.1236252

Full text not available from this repository.

Abstract

This paper considers an approach to mesh denoising based on the concept of random walks. The proposed method consists of two stages: a face normal filtering procedure, followed by a vertex position updating procedure which integrates the denoised face normals in a least-squares sense. Face normal filtering is performed by weighted averaging of normals in a neighbourhood. The weights are based on the probability of arriving at a given neighbour after a random walk of a virtual particle starting at a given face of the mesh and moving a fixed number of steps. The probability of a particle stepping from its current face to a given neighboring face is determined by the angle between the two face normals, using a Gaussian distribution whose width is adaptively adjusted to enhance the feature-preserving property of the algorithm. The vertex position updating procedure uses the conjugate gradient algorithm for speed of convergence. Analysis and experiments show that random walks of different step lengths yield similar denoising results. In particular, iterative application of a one-step random walk in a progressive manner effectively preserves detailed features while denoising the mesh very well. We observe that this approach is faster than many other feature-preserving mesh denoising algorithms.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	feature preservation, mesh denoising, mesh smoothing, random walk
Publisher:	Association for Computing Machinery
ISBN:	9781595936660; 1595936661
Last Modified:	17 Oct 2022 09:41
URI:	https://orca.cardiff.ac.uk/id/eprint/5221

Citation Data

Cited 13 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item