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      Reverse engineering of CAD models via clustering and approximate implicitization

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          Abstract

          In applications like computer aided design, geometric models are often represented numerically as polynomial splines or NURBS, even when they originate from primitive geometry. For purposes such as redesign and isogeometric analysis, it is of interest to extract information about the underlying geometry through reverse engineering. In this work we develop a novel method to determine these primitive shapes by combining clustering analysis with approximate implicitization. The proposed method is automatic and can recover algebraic hypersurfaces of any degree in any dimension. In exact arithmetic, the algorithm returns exact results. All the required parameters, such as the implicit degree of the patches and the number of clusters of the model, are inferred using numerical approaches in order to obtain an algorithm that requires as little manual input as possible. The effectiveness, efficiency and robustness of the method are shown both in a theoretical analysis and in numerical examples implemented in Python.

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          Overview of Supervised Learning

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            Reverse engineering and design recovery: a taxonomy

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              Reverse engineering of geometric models—an introduction

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                Author and article information

                Journal
                17 October 2018
                Article
                1810.07451
                9fec23f7-5d56-42d7-a20b-2652a566302b

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                65D17, 68U17, 62H30
                math.NA cs.GR cs.LG stat.ML

                Numerical & Computational mathematics,Machine learning,Artificial intelligence,Graphics & Multimedia design

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