RANSAC for Aligned Planes with Application to Roof Plane Detection in Point Clouds
Steffen Goebbels, Regina Pohle-Fröhlich
2020
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.
DownloadPaper Citation
in Harvard Style
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 (VISIGRAPP 2020) - Volume 1: GRAPP; ISBN 978-989-758-402-2, SciTePress, pages 193-200. DOI: 10.5220/0008836301930200
in Bibtex Style
@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 (VISIGRAPP 2020) - Volume 1: GRAPP},
year={2020},
pages={193-200},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008836301930200},
isbn={978-989-758-402-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - 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
PB - SciTePress