基于加权平方体积最小化的均匀四面体网格生成方法。

Kaixin Yu, Yifu Wang, Peng Song, Xiangqiao Meng, Ying He, Jianjun Chen
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引用次数: 0

摘要

提出了一种由封闭三角形网格生成高质量四面体网格的新算法——加权平方体积最小化(WSVM)。从最小化表面积平方的最小曲面原理中获得灵感,WSVM采用了一种新的能量函数,对四面体元素的加权平方体积进行积分。当以恒定的重量最小化时,这种能量促进四面体之间的均匀体积。调整权重以考虑局部几何进一步实现网格内均匀的二面角。该算法首先通过Delaunay四面体化生成初始四面体网格,然后依次最小化面向体积的能量,然后最小化面向二面体角的能量。在每个阶段,它在优化顶点位置和通过迭代过程改进网格连接之间交替进行。该算法完全自动运行,无需参数调整。对各种3D模型的评估表明,与现有方法相比,WSVM始终能够产生更高质量的四面体网格,并且条数更少,均匀性更高。在项目网页上查看更多细节:https://kaixinyu-hub.github.io/WSVM.github.io/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weighted Squared Volume Minimization (WSVM) for Generating Uniform Tetrahedral Meshes.

This paper presents a new algorithm, Weighted Squared Volume Minimization (WSVM), for generating high-quality tetrahedral meshes from closed triangle meshes. Drawing inspiration from the principle of minimal surfaces that minimize squared surface area, WSVM employs a new energy function integrating weighted squared volumes for tetrahedral elements. When minimized with constant weights, this energy promotes uniform volumes among the tetrahedra. Adjusting the weights to account for local geometry further achieves uniform dihedral angles within the mesh. The algorithm begins with an initial tetrahedral mesh generated via Delaunay tetrahedralization and proceeds by sequentially minimizing volume-oriented and then dihedral angle-oriented energies. At each stage, it alternates between optimizing vertex positions and refining mesh connectivity through the iterative process. The algorithm operates fully automatically and requires no parameter tuning. Evaluations on a variety of 3D models demonstrate that WSVM consistently produces tetrahedral meshes of higher quality, with fewer slivers and enhanced uniformity compared to existing methods. Check out further details at the project webpage: https://kaixinyu-hub.github.io/WSVM.github.io/.

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