publication . Article . Preprint . 2018

mesh denoising based on normal voting tensor and binary optimization

Sunil Kumar Yadav; Ulrich Reitebuch; Konrad Polthier;
Open Access
  • Published: 01 Aug 2018 Journal: IEEE Transactions on Visualization and Computer Graphics, volume 24, pages 2,366-2,379 (issn: 1077-2626, eissn: 2160-9306, Copyright policy)
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
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...
Subjects
ACM Computing Classification System: ComputingMethodologies_COMPUTERGRAPHICS
free text keywords: Artificial intelligence, business.industry, business, Stress (mechanics), Binary number, Stochastic process, Computer vision, Geometry processing, Noise measurement, Mathematical optimization, Computer science, Smoothing, Noise reduction, Algorithm, Tensor, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, Mathematics - Differential Geometry
Related Organizations
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publication . Article . Preprint . 2018

mesh denoising based on normal voting tensor and binary optimization

Sunil Kumar Yadav; Ulrich Reitebuch; Konrad Polthier;