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arXiv · 1807.08304

Deep Learning Parametrization for B-Spline Curve Approximation

Pascal Laube·Matthias O. Franz·Georg Umlauf
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Abstract

In this paper we present a method using deep learning to compute parametrizations for B-spline curve approximation. Existing methods consider the computation of parametric values and a knot vector as separate problems. We propose to train interdependent deep neural networks to predict parametric values and knots. We show that it is possible to include B-spline curve approximation directly into the neural network architecture. The resulting parametrizations yield tight approximations and are able to outperform state-of-the-art methods.

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BibTeXRIS

Pascal Laube, Matthias O. Franz, Georg Umlauf. 2018-07-22. Deep Learning Parametrization for B-Spline Curve Approximation. https://arxiv.org/abs/1807.08304

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