Toward a Real Time View-invariant 3D Action Recognition

Mounir Hammouche, Enjie Ghorbel, Anthony Fleury, Sébastien Ambellouis

Abstract

In this paper we propose a novel human action recognition method, robust to viewpoint variation, which combines skeleton- and depth-based action recognition approaches. For this matter, we first build several base classifiers, to independently predict the action performed by a subject. Then, two efficient combination strategies, that take into account skeleton accuracy and human body orientation, are proposed. The first is based on fuzzy switcher where the second uses a combination between fuzzy switcher and aggregation. Moreover, we introduce a new algorithm for the estimation of human body orientation. To perform the test we have created a new Multiview 3D Action public dataset with three viewpoint angles (30°,0°,-30°). The experimental results show that an efficient combination strategy of base classifiers improves the accuracy and the computational efficiency for human action recognition.

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Paper Citation


in Harvard Style

Hammouche M., Ghorbel E., Fleury A. and Ambellouis S. (2016). Toward a Real Time View-invariant 3D Action Recognition . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISION4HCI, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 745-754. DOI: 10.5220/0005843607450754


in Bibtex Style

@conference{vision4hci16,
author={Mounir Hammouche and Enjie Ghorbel and Anthony Fleury and Sébastien Ambellouis},
title={Toward a Real Time View-invariant 3D Action Recognition},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISION4HCI, (VISIGRAPP 2016)},
year={2016},
pages={745-754},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005843607450754},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISION4HCI, (VISIGRAPP 2016)
TI - Toward a Real Time View-invariant 3D Action Recognition
SN - 978-989-758-175-5
AU - Hammouche M.
AU - Ghorbel E.
AU - Fleury A.
AU - Ambellouis S.
PY - 2016
SP - 745
EP - 754
DO - 10.5220/0005843607450754