Mesh Denoising based on Normal Voting Tensor and Binary Optimization

Autor:	Yadav, S. K., Reitebuch, U., Polthier, K.
Rok vydání:	2016
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Graphics Mathematics - Differential Geometry
Druh dokumentu:	Working Paper
DOI:	10.1109/TVCG.2017.2740384
Popis:	This paper presents a tensor multiplication based smoothing algorithm that follows a two step denoising method. 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 and visual results demonstrate the performance our method is better compared to state of the art smoothing approaches. Comment: 13 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1607.07427 Zobrazit plný text záznamu View this record from Arxiv