2004•Keisan Rikigaku Koenkai koen ronbunshu/Keisan Rikigaku Kouenkai kouen rombunshuuOpen access

Development of the surface mesh quality improvement algorithm

Maria Savchenko, Olga Vladimirovna Egorova, Ichiro Hagiwara, Владимир Васильевич Савченко

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Abstract

In this paper, we present mesh improvement algorithms based on quasi-statistical modeling. A mesh quality parameter is modeled as a random variable with the desirable distribution based on an initial topology of the mesh. The goal of the presented research is to improve the polygonal mesh by producing the mesh elements with a Gaussian (normal) distribution of the mesh quality parameter values.

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What this paper is about

In this paper, we present mesh improvement algorithms based on quasi-statistical modeling. A mesh quality parameter is modeled as a random variable with the desirable distribution based on an initial topology of the mesh. The goal of the presented research is to improve the polygonal mesh by producing the mesh elements with a Gaussian (normal) distribution of the mesh quality parameter values.

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Available abstract

In this paper, we present mesh improvement algorithms based on quasi-statistical modeling. A mesh quality parameter is modeled as a random variable with the desirable distribution based on an initial topology of the mesh. The goal of the presented research is to improve the polygonal mesh by producing the mesh elements with a Gaussian (normal) distribution of the mesh quality parameter values.

Key concepts: Laplacian smoothing, T-vertices, Computer science, Gaussian, Algorithm, Triangle mesh, Distribution (mathematics), Mesh generation

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