Isotropic Remeshing by Dynamic Voronoi Tessellation on Voxelized Surface

Ashutosh Soni, Partha Bhowmick
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Abstract

A novel algorithm for isotropic remeshing of a triangle mesh is presented in this paper. The algorithm is designed to work on a voxelized surface and integrates several novel ideas. One such is the notion of functional partitioning that aids in uniform distribution of seeds for initializing the process of dynamic Voronoi tessellation (DVT). The concept of DVT is also novel and found to be quite effective for iteratively transforming the input mesh into an isotropic mesh while keeping the tessellation aligned with the surface geometry. In each iteration, a Voronoi energy field is used to rearrange the seeds and to recreate the DVT. Over successive iterations, the DVT is found to keep on improving the mesh isotropy without compromising with the surface features. The Delaunay triangles corresponding to the final tessellation are further subdivided in high-curvature regions. The resultant mesh is finally projected back onto the original mesh in order to minimize the Hausdorff error. As our algorithm works in voxel space, it is readily implementable in GPU. Experimental results on various datasets demonstrate its efficiency and robustness.
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体素化表面上动态Voronoi镶嵌的各向同性网格重划分
提出了一种新的三角形网格各向同性重划分算法。该算法被设计用于体素化表面,并集成了一些新颖的思想。其中一个是功能划分的概念,它有助于种子的均匀分布,以初始化动态Voronoi镶嵌(DVT)过程。DVT的概念也是新颖的,并且被发现对于迭代地将输入网格转换为各向同性网格同时保持镶嵌与表面几何形状对齐是非常有效的。在每次迭代中,Voronoi能量场被用来重新排列种子并重建DVT。在连续迭代中,发现DVT在不影响表面特征的情况下不断改善网格各向同性。与最终镶嵌相对应的德劳内三角形在高曲率区域进一步细分。最后将生成的网格投影回原始网格,以最小化Hausdorff误差。由于我们的算法在体素空间中工作,因此很容易在GPU上实现。在不同数据集上的实验结果证明了该方法的有效性和鲁棒性。
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