Fitting $C^1$ Surfaces to Scattered Data with $S^1_2(∆^{(2)}_{m,n})$

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Abstract

This paper presents a fast algorithm (BS2 Algorithm) for fitting $C^1$ surfaces to scattered data points. By using energy minimization, the bivariate spline space $S^1_2(∆^{(2)}_{m,n})$ is introduced to construct a $C^1$-continuous piecewise quadratic surface through a set of irregularly 3D points. Moreover, a multilevel method is also presented. Some experimental results show that the accuracy is satisfactory. Furthermore, the BS2 Algorithm is more suitable for fitting surfaces if the given data points have some measurement errors.

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DOI

10.4208/jcm.1101-m3203

How to Cite

Fitting $C^1$ Surfaces to Scattered Data with $S^1_2(∆^{(2)}_{m,n})$. (2018). Journal of Computational Mathematics, 29(4), 396-414. https://doi.org/10.4208/jcm.1101-m3203