# Mesh Denoising based on Normal Voting Tensor and Binary Optimization

Source: [Mesh Denoising based on Normal Voting Tensor and Binary Optimization](<https://www.sota2.com/research/paper/68fa541c1e209131ce988fcc>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T12:50:27.829Z

Authors: S. K. Yadav, U. Reitebuch, K. Polthier

Published: 2016-07-20T20:39:37.000Z

## 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 compared to state of the art smoothing approaches.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1607.07427>)

[PDF](<https://arxiv.org/pdf/1607.07427.pdf>)