publication . Preprint . Article . 2016

Mesh Denoising based on Normal Voting Tensor and Binary Optimization

Sunil Kumar Yadav; Ulrich Reitebuch; Konrad Polthier;
Open Access English
  • Published: 20 Jul 2016
Abstract
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 compar...
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Subjects
ACM Computing Classification System: ComputingMethodologies_COMPUTERGRAPHICS
free text keywords: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, Mathematics - Differential Geometry, Signal Processing, Software, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Noise measurement, Smoothing, Mathematical optimization, Noise reduction, Binary number, Stress (mechanics), Algorithm, Geometry processing, Stochastic process, Tensor, Computer science
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