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Authors: Serhan Cosar ; Claudio Coppola and Nicola Bellotto

Affiliation: University of Lincoln, United Kingdom

Keyword(s): Re-identification, Volume-based Features, Occlusion, Body Motion, Service Robots.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Pattern Recognition ; Robotics ; Software Engineering

Abstract: This paper presents an RGB-D based human re-identification approach using novel biometrics features from the body’s volume. Existing work based on RGB images or skeleton features have some limitations for real-world robotic applications, most notably in dealing with occlusions and orientation of the user. Here, we propose novel features that allow performing re-identification when the person is facing side/backward or the person is partially occluded. The proposed approach has been tested for various scenarios including different views, occlusion and the public BIWI RGBD-ID dataset.

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Paper citation in several formats:
Cosar, S.; Coppola, C. and Bellotto, N. (2017). Volume-based Human Re-identification with RGB-D Cameras. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP; ISBN 978-989-758-225-7; ISSN 2184-4321, SciTePress, pages 389-397. DOI: 10.5220/0006155403890397

@conference{visapp17,
author={Serhan Cosar. and Claudio Coppola. and Nicola Bellotto.},
title={Volume-based Human Re-identification with RGB-D Cameras},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP},
year={2017},
pages={389-397},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006155403890397},
isbn={978-989-758-225-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 4: VISAPP
TI - Volume-based Human Re-identification with RGB-D Cameras
SN - 978-989-758-225-7
IS - 2184-4321
AU - Cosar, S.
AU - Coppola, C.
AU - Bellotto, N.
PY - 2017
SP - 389
EP - 397
DO - 10.5220/0006155403890397
PB - SciTePress

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