Weighted Squared Volume Minimization (WSVM) for Generating Uniform Tetrahedral Meshes

Kaixin Yu, Yifu Wang, Peng Song, Xiangqiao Meng, Ying He, Jianjun Chen
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Abstract

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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生成统一四面体网格的加权平方体积最小化(WSVM)
本文提出了一种从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)。WSVM 从最小化平方表面积的最小曲面原理中汲取灵感,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。当以恒定权重最小化时,该能量可促进四面体之间的体积一致。根据局部几何形状调整权重可进一步实现网格内统一的二面体。该算法从通过 Delaunay 四面体化生成的初始四面体网格开始,依次最小化面向体积的能量和面向二面角的能量。在每个阶段,它都会交替优化顶点位置,并通过迭代过程完善网格连接性。该算法完全自动运行,无需调整参数。在各种三维模型上进行的评估表明,与现有方法相比,WSVM 能持续生成质量更高的四面体网格,减少切片,提高均匀性。欲了解更多详情,请访问项目网页: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。
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