PowerRTF: Power Diagram based Restricted Tangent Face for Surface Remeshing
PowerRTF: Power Diagram based Restricted Tangent Face for Surface Remeshing
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DOI：
10.1111/cgf.14897
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发表时间：
2023-08
影响因子：
2.5
通讯作者：
Yuyou Yao;J. Liu;Yue Fei;Wenming Wu;Gaofeng Zhang;Dong‐Ming Yan;Liping Zheng
中科院分区：
文献类型：
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作者：
Yuyou Yao;J. Liu;Yue Fei;Wenming Wu;Gaofeng Zhang;Dong‐Ming Yan;Liping Zheng
上级质量的三角形网格对于实际应用中的几何处理具有重要意义。现有的基于CVT的近似网格重划分方法使用平面多边形面片来拟合原始曲面，从而简化了计算复杂度。然而，它们通常不考虑曲面曲率。拓扑误差和野值也可能出现在封闭曲面的网格重划分中，导致错误的网格。在这方面，我们提出了一种新的方法命名为PowerRTF，限制的切面（RTF）结合功率图的扩展，以更好地近似原始曲面的曲率自适应。其思想是为每个采样点引入权重属性，并计算切面上的幂图，以生成面积受控的多边形小平面。在此基础上，我们对PowerRTF施加了可变容量约束和质心约束，提供了网格质量和计算效率之间的权衡。此外，我们采用了一个正常的验证为基础的反侧点剔除方法，以解决在封闭的片材表面重新网格化的拓扑错误和离群值。我们的方法独立地计算和优化每个采样点的PowerRTF，这是有效地在GPU上并行实现。实验结果表明，我们的方法的有效性，灵活性和效率。
Triangular meshes of superior quality are important for geometric processing in practical applications. Existing approximative CVT‐based remeshing methodology uses planar polygonal facets to fit the original surface, simplifying the computational complexity. However, they usually do not consider surface curvature. Topological errors and outliers can also occur in the close sheet surface remeshing, resulting in wrong meshes. With this regard, we present a novel method named PowerRTF, an extension of the restricted tangent face (RTF) in conjunction with the power diagram, to better approximate the original surface with curvature adaption. The idea is to introduce a weight property to each sample point and compute the power diagram on the tangent face to produce area‐controlled polygonal facets. Based on this, we impose the variable‐capacity constraint and centroid constraint to the PowerRTF, providing the trade‐off between mesh quality and computational efficiency. Moreover, we apply a normal verification‐based inverse side point culling method to address the topological errors and outliers in close sheet surface remeshing. Our method independently computes and optimizes the PowerRTF per sample point, which is efficiently implemented in parallel on the GPU. Experimental results demonstrate the effectiveness, flexibility, and efficiency of our method.