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Authors: Jacek Komorowski ; Grzegorz Kurzejamski ; Monika Wysoczańska and Tomasz Trzcinski

Affiliation: Warsaw University of Technology, Warsaw, Poland

Keyword(s): Place Recognition, 3D Point Cloud, RGB-D, Deep Metric Learning.

Abstract: This paper presents an approach for learning-based discriminative 3D point cloud descriptor from RGB-D images for place recognition purposes in indoor environments. Existing methods, such as such as PointNetVLAD, PCAN or LPD-Net, are aimed at outdoor environments and operate on 3D point clouds from LiDAR. They are based on PointNet architecture and designed to process only the scene geometry and do not consider appearance (RGB component). In this paper we present a place recognition method based on sparse volumetric representation and processing scene appearance in addition to the geometry. We also investigate if using two modalities, appearance (RGB data) and geometry (3D structure), improves discriminativity of a resultant global descriptor.

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Paper citation in several formats:
Komorowski, J.; Kurzejamski, G.; Wysoczańska, M. and Trzcinski, T. (2021). Global Point Cloud Descriptor for Place Recognition in Indoor Environments. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 216-224. DOI: 10.5220/0010340502160224

@conference{visapp21,
author={Jacek Komorowski. and Grzegorz Kurzejamski. and Monika Wysoczańska. and Tomasz Trzcinski.},
title={Global Point Cloud Descriptor for Place Recognition in Indoor Environments},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={216-224},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010340502160224},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - Global Point Cloud Descriptor for Place Recognition in Indoor Environments
SN - 978-989-758-488-6
IS - 2184-4321
AU - Komorowski, J.
AU - Kurzejamski, G.
AU - Wysoczańska, M.
AU - Trzcinski, T.
PY - 2021
SP - 216
EP - 224
DO - 10.5220/0010340502160224
PB - SciTePress

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