高斯-赛德尔渐进迭代逼近(GS-PIA)用于环面插值

Zhihao Wang, Yajuan Li, Weiyin Ma, Chongyang Deng
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引用次数: 2

摘要

将传统的线性系统高斯-塞德尔迭代法与数据插值的渐进迭代逼近法相结合,提出了一种用于循环细分曲面插值的高斯-塞德尔渐进迭代逼近法。利用矩阵理论证明了GS-PIA是收敛的。GS-PIA算法保留了经典PIA方法的优点,如与给定网格的相似性以及局部方法和全局方法的优点。与现有的细分曲面插值方法相比,GS-PIA算法具有三个方面的优势。首先,与PIA和WPIA算法相比,它具有更快的收敛速度。其次,与WPIA算法相比,GS-PIA算法不需要选择权重。第三,与其他具有公平性措施的方法相比,GS-PIA无需修改网格拓扑结构。文中给出了环细分曲面插值的数值算例,说明了GS-PIA算法的效率和有效性。•计算方法→参数化曲线和曲面模型;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gauss-Seidel Progressive Iterative Approximation (GS-PIA) for Loop Surface Interpolation
We propose a Gauss-Seidel progressive iterative approximation (GS-PIA) method for Loop subdivision surface interpolation by combining classical Gauss-Seidel iterative method for linear system and progressive iterative approximation (PIA) for data interpolation. We prove that GS-PIA is convergent by applying matrix theory. GS-PIA algorithm retains the good features of the classical PIA method, such as the resemblance with the given mesh and the advantages of both a local method and a global method. Compared with some existed interpolation methods of subdivision surfaces, GS-PIA algorithm has advantages in three aspects. First, it has a faster convergence rate compared with the PIA and WPIA algorithms. Second, compared with WPIA algorithm, GS-PIA algorithm need not to choose weights. Third, GS-PIA need not to modify the mesh topology compared with other methods with fairness measures. Numerical examples for Loop subdivision surfaces interpolation illustrated in this paper show the efficiency and effectiveness of GS-PIA algorithm. CCS Concepts •Computing methodologies → Parametric curve and surface models;
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