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Authors: Tekla Tóth and Levente Hajder

Affiliation: Department of Algorithm and Applications, Eötvös Loránd University, Pázmány Péter stny. 1/C, Budapest 1117 and Hungary

Keyword(s): Surface Fitting, Geometric Primitives, Light Detection and Ranging, Robust Fitting.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image Formation and Preprocessing ; Multimodal and Multi-Sensor Models of Image Formation

Abstract: This paper deals with robust surface fitting on spatial points measured by a LiDAR device. The point clouds contain hundreds of thousands data points. Therefore, the time demand of the algorithms is crucial for fast operation. We present two novel algorithms based on the RANSAC method: one for plane detection and one for other object detection. The execution time of the novel algorithms is significantly lower as only one random sampling is required because a deterministic teqnique selects the other data points. The accuracy of the novel methods are validated on synthesized data as well as real indoor and outdoor measurements.

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Paper citation in several formats:
Tóth, T. and Hajder, L. (2019). Robust Fitting of Geometric Primitives on LiDAR Data. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 622-629. DOI: 10.5220/0007572606220629

@conference{visapp19,
author={Tekla Tóth. and Levente Hajder.},
title={Robust Fitting of Geometric Primitives on LiDAR Data},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={622-629},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007572606220629},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Robust Fitting of Geometric Primitives on LiDAR Data
SN - 978-989-758-354-4
IS - 2184-4321
AU - Tóth, T.
AU - Hajder, L.
PY - 2019
SP - 622
EP - 629
DO - 10.5220/0007572606220629
PB - SciTePress

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