Authors: E Carlini R Ferretti
Publish Date: 2016/12/21
Volume: 18, Issue: 2-3, Pages: 103-112
Abstract
We propose a SemiLagrangian scheme coupled with Radial Basis Function interpolation for approximating a curvaturerelated level set model which has been proposed by Zhao et al Comput Vis Image Underst 80295–319 2000 to reconstruct unknown surfaces from sparse data sets The main advantages of the proposed scheme are the possibility to solve the level set method on unstructured grids as well as to concentrate the reconstruction points in the neighbourhood of the data set with a consequent reduction of the computational effort Moreover the scheme is explicit Numerical tests show the accuracy and robustness of our approach to reconstruct curves and surfaces from relatively sparse data sets
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