Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Random walks for feature-preserving mesh denoising

Sun, Xianfang, Rosin, Paul L., Martin, Ralph Robert and Langbein, Frank Curd 2009. Random walks for feature-preserving mesh denoising. Computer Aided Geometric Design 25 (7) , pp. 437-456. 10.1016/j.cagd.2007.12.008

[img]
Preview
PDF - Submitted Pre-Print Version
Download (1MB) | Preview

Abstract

An approach to mesh denoising based on the concept of random walks is examined. The proposed method consists of two stages: face normal filtering, followed by vertex position updating to integrate the denoised face normals in a least-squares manner. Face normal filtering is performed by weighted averaging of normals in a neighbourhood. A novel approach to determining weights is to compute the probability of arriving at each neighbour following a fixed-length random walk of a virtual particle starting at a given face of the mesh. The probability of the particle stepping from its current face to some neighbouring face is a function of the angle between the two face normals, based on a Gaussian distribution whose variance 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. Our experiments show that, in fact, iterative application of a one-step random walk in a progressive manner effectively preserves detailed features while denoising the mesh very well. This approach is faster than many other feature-preserving mesh denoising algorithms.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
Uncontrolled Keywords: Mesh denoising ; Mesh smoothing ; Random walk ; Feature preservation
Additional Information: PDF uploaded in accordance with publisher's policy http://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy [accessed 30/03/2015] NOTICE: this is the author’s version of a work that was accepted for publication in Computer Aided Geometric Design. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Aided Geometric Design, [VOL 25, ISSUE 7, 2009] DOI 10.1016/j.cagd.2007.12.008
Publisher: Elsevier
ISSN: 0167-8396
Last Modified: 03 Jan 2018 00:24
URI: http://orca.cf.ac.uk/id/eprint/5284

Citation Data

Cited 32 times in Google Scholar. View in Google Scholar

Cited 59 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics