Mesh clustering by approximating centroidal Voronoi tessellation

Fengtao Fan, F. Cheng, Conglin Huang, Yong Li, Jianzhong Wang, S. Lai
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引用次数: 4

Abstract

An elegant and efficient mesh clustering algorithm is presented. The faces of a polygonal mesh are divided into different clusters for mesh coarsening purpose by approximating the Centroidal Voronoi Tessellation of the mesh. The mesh coarsening process after clustering can be done in an isotropic or anisotropic fashion. The presented algorithm improves previous techniques in local geometric operations and parallel updates. The new algorithm is very simple but is guaranteed to converge, and generates better approximating meshes with the same computation cost. Moreover, the new algorithm is suitable for the variational shape approximation problem with L2, 1 distortion error metric and the convergence is guaranteed. Examples demonstrating efficiency of the new algorithm are also included in the paper.
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通过逼近质心Voronoi镶嵌的网格聚类
提出了一种简洁高效的网格聚类算法。通过逼近多边形网格的质心Voronoi镶嵌,将多边形网格的面划分为不同的簇,达到网格粗化的目的。聚类后的网格粗化过程可以采用各向同性或各向异性的方式进行。该算法在局部几何运算和并行更新方面改进了原有的算法。该算法在保证收敛性的同时,简化了算法,并在相同的计算代价下生成了更好的逼近网格。该算法适用于具有L2、1畸变误差度量的变分形状逼近问题,并保证了算法的收敛性。文中还给出了一些实例,证明了新算法的有效性。
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