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Authors: Markus Friedrich 1 ; Steffen Illium 1 ; Pierre-Alain Fayolle 2 and Claudia Linnhoff-Popien 1

Affiliations: 1 Institute for Computer Science, LMU Munich, Oettingenstraße 67, Munich, Germany ; 2 The University of Aizu, Ikki machi, Aizu-Wakamatsu, Japan

Keyword(s): 3D Computer Vision, Deep Learning, Evolutionary Computing, Fitting, RANSAC, Segmentation.

Abstract: The segmentation and fitting of solid primitives to 3D point clouds is a complex task. Existing systems are restricted either in the number of input points or the supported primitive types. This paper proposes a hybrid pipeline that is able to reconstruct spheres, bounded cylinders and rectangular cuboids on large point sets. It uses a combination of deep learning and classical RANSAC for primitive fitting, a DBSCAN-based clustering scheme for increased stability and a specialized Genetic Algorithm for robust cuboid extraction. In a detailed evaluation, its performance metrics are discussed and resulting solid primitive sets are visualized. The paper concludes with a discussion of the approach’s limitations.

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Paper citation in several formats:
Friedrich, M.; Illium, S.; Fayolle, P. and Linnhoff-Popien, C. (2020). A Hybrid Approach for Segmenting and Fitting Solid Primitives to 3D Point Clouds. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - GRAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 38-48. DOI: 10.5220/0008870600380048

@conference{grapp20,
author={Markus Friedrich. and Steffen Illium. and Pierre{-}Alain Fayolle. and Claudia Linnhoff{-}Popien.},
title={A Hybrid Approach for Segmenting and Fitting Solid Primitives to 3D Point Clouds},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - GRAPP},
year={2020},
pages={38-48},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008870600380048},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - GRAPP
TI - A Hybrid Approach for Segmenting and Fitting Solid Primitives to 3D Point Clouds
SN - 978-989-758-402-2
IS - 2184-4321
AU - Friedrich, M.
AU - Illium, S.
AU - Fayolle, P.
AU - Linnhoff-Popien, C.
PY - 2020
SP - 38
EP - 48
DO - 10.5220/0008870600380048
PB - SciTePress

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