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.

Download


Paper 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