Feature-preserving mesh denoising based on vertices classification

Authors:
Zhe Bian;Ruofeng Tong
Affiliations:
Tsinghua National Laboratory for Information Science and Technology, China and Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;Institute of Artificial Intelligence, Zhejiang University, Hangzhou 310027, China
Venue:
Computer Aided Geometric Design
Year:
2011

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Abstract

In this paper, we present an effective surface denoising method for noisy surfaces. The two key steps in this method involve feature vertex classification and an iterative, two-step denoising method depending on two feature weighting functions. The classification for feature vertices is based on volume integral invariant. With the super nature of this integral invariant, the features of vertices can be fixed with less influence of noise, and different denoising degrees can be applied to different parts of the pending surface. Compared with other methods, our approach produces better results in feature-preserving.