Abstract
A general algorithm framework for 3D mesh parametrization is proposed in this paper. Under this framework, a parametrization algorithm is divided into three steps. In the first step, the linearly reconstructing weights of each vertex with respect to its neighbours are computed. These weights are then used to computed a initial parametrization mesh, and in the third step, this initial mesh is rotated and scaled to obtain a parametrization mesh with high isometric precision. Four parametrization algorithms are proposed based on this framework. Examples show the effectiveness and applicability of the parametrization algorithms proposed in the paper.
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Sun, X., Hancock, E.R. (2005). Locally Linear Isometric Parameterization. In: Rangarajan, A., Vemuri, B., Yuille, A.L. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2005. Lecture Notes in Computer Science, vol 3757. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11585978_36
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DOI: https://doi.org/10.1007/11585978_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30287-2
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