期刊
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
卷 24, 期 8, 页码 2366-2379出版社
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2017.2740384
关键词
Geometry processing; mesh smoothing; normal voting tensor; eigenvalue binary optimization; noise analysis
资金
- Dahlem Research School (DRS)
- German Federal Ministry of Education and Research (BMBF Neu2 ADVISIMS)
This paper presents a two-stage mesh denoising algorithm. Unlike other traditional averaging approaches, our approach uses an element-based normal voting tensor to compute smooth surfaces. By introducing a binary optimization on the proposed tensor together with a local binary neighborhood concept, our algorithm better retains sharp features and produces smoother umbilical regions than previous approaches. On top of that, we provide a stochastic analysis on the different kinds of noise based on the average edge length. The quantitative results demonstrate that the performance of our method is better compared to state-of-the-art smoothing approaches.
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