Machine learning methods for reverse engineering of defective structured surfaces

Machine learning methods for reverse engineering of defective structured surfaces

Author
Pascal Laube
Publication Year
2020
Publisher
Springer
Language
English
Document Type
Book
Faculty / Subject Heading
Computer Science

Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.


Keywords: Computer science / Machine Learning Methods / CaD Reverse Engineering / Defective Structured Surfaces / Surface Reconstruction / Geometric Modeling / Surface Approximation / Surface Parametrization