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Authors: Steffen Goebbels and Regina Pohle-Fröhlich

Affiliation: Institute for Pattern Recognition, Faculty of Electrical Engineering and Computer Science, Niederrhein University of Applied Sciences, Reinarzstr. 49, 47805 Krefeld, Germany

ISBN: 978-989-758-402-2

ISSN: 2184-4321

Keyword(s): RANSAC, Building Reconstruction, CityGML.

Abstract: Random Sample Consensus (RANSAC) is a standard algorithm to recognize planes in point clouds. It does not require additional context information. However, it might be applied in situations where results can be improved based on domain knowledge. Such a situation is 3D building reconstruction from airborne laser scanning data. The normals of many roof facets are orthogonal to footprint vectors. This specific property helps to estimate roof planes more precisely. The paper describes the adapted RANSAC algorithm. It can be also used in other applications in which planes are aligned to supporting vectors.

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Paper citation in several formats:
Goebbels, S. and Pohle-Fröhlich, R. (2020). RANSAC for Aligned Planes with Application to Roof Plane Detection in Point Clouds.In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP, ISBN 978-989-758-402-2, ISSN 2184-4321, pages 193-200. DOI: 10.5220/0008836301930200

@conference{grapp20,
author={Steffen Goebbels. and Regina Pohle{-}Fröhlich.},
title={RANSAC for Aligned Planes with Application to Roof Plane Detection in Point Clouds},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,},
year={2020},
pages={193-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008836301930200},
isbn={978-989-758-402-2},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP,
TI - RANSAC for Aligned Planes with Application to Roof Plane Detection in Point Clouds
SN - 978-989-758-402-2
AU - Goebbels, S.
AU - Pohle-Fröhlich, R.
PY - 2020
SP - 193
EP - 200
DO - 10.5220/0008836301930200

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