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Authors: Benjamin Kelényi ; Szilárd Molnár and Levente Tamás

Affiliation: Department of Automation, Technical University of Cluj-Napoca, Memorandumului St. 28, 400114 Cluj-Napoca, Romania

Keyword(s): Time of Flight, 3D Point Clouds, Mobile Robots, Embedded Devices, Depth Image Processing.

Abstract: The main goal of this work is to analyze the most suitable methods for segmenting and classifying 3D point clouds using embedded GPU for mobile robots. We review the current main approaches including, the point-based, voxel-based and point-voxel-based methods. We evaluated the selected algorithms on different publicly available datasets. Simultaneously, we created a novel architecture based on point-voxel CNN architecture that combines depth imaging with IR. This architecture was designed particularly for pulse-based Time of Flight (ToF) cameras and the primary algorithm’s target being embedded devices. We tested the proposed algorithm on custom indoor/outdoor and public datasets, using different camera vendors.

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Paper citation in several formats:
Kelényi, B.; Molnár, S. and Tamás, L. (2022). 3D Object Recognition using Time of Flight Camera with Embedded GPU on Mobile Robots. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 849-856. DOI: 10.5220/0010972200003124

@conference{visapp22,
author={Benjamin Kelényi. and Szilárd Molnár. and Levente Tamás.},
title={3D Object Recognition using Time of Flight Camera with Embedded GPU on Mobile Robots},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={849-856},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010972200003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - 3D Object Recognition using Time of Flight Camera with Embedded GPU on Mobile Robots
SN - 978-989-758-555-5
IS - 2184-4321
AU - Kelényi, B.
AU - Molnár, S.
AU - Tamás, L.
PY - 2022
SP - 849
EP - 856
DO - 10.5220/0010972200003124
PB - SciTePress

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