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Authors: Enjie Ghorbel ; Konstantinos Papadopoulos ; Renato Baptista ; Himadri Pathak ; Girum Demisse ; Djamila Aouada and Björn Ottersten

Affiliation: Interdisciplinary Centre for Security, Reliability and Trust, Luxembourg

ISBN: 978-989-758-354-4

Keyword(s): View-invariant, Human Action Recognition, Monocular Camera, Pose Estimation.

Abstract: View-invariant action recognition using a single RGB camera represents a very challenging topic due to the lack of 3D information in RGB images. Lately, the recent advances in deep learning made it possible to extract a 3D skeleton from a single RGB image. Taking advantage of this impressive progress, we propose a simple framework for fast and view-invariant action recognition using a single RGB camera. The proposed pipeline can be seen as the association of two key steps. The first step is the estimation of a 3D skeleton from a single RGB image using a CNN-based pose estimator such as VNect. The second one aims at computing view-invariant skeleton-based features based on the estimated 3D skeletons. Experiments are conducted on two well-known benchmarks, namely, IXMAS and Northwestern-UCLA datasets. The obtained results prove the validity of our concept, which suggests a new way to address the challenge of RGB-based view-invariant action recognition.

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Paper citation in several formats:
Ghorbel, E.; Papadopoulos, K.; Baptista, R.; Pathak, H.; Demisse, G.; Aouada, D. and Ottersten, B. (2019). A View-invariant Framework for Fast Skeleton-based Action Recognition using a Single RGB Camera.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 573-582. DOI: 10.5220/0007524405730582

@conference{visapp19,
author={Enjie Ghorbel. and Konstantinos Papadopoulos. and Renato Baptista. and Himadri Pathak. and Girum Demisse. and Djamila Aouada. and Björn Ottersten.},
title={A View-invariant Framework for Fast Skeleton-based Action Recognition using a Single RGB Camera},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={573-582},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007524405730582},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - A View-invariant Framework for Fast Skeleton-based Action Recognition using a Single RGB Camera
SN - 978-989-758-354-4
AU - Ghorbel, E.
AU - Papadopoulos, K.
AU - Baptista, R.
AU - Pathak, H.
AU - Demisse, G.
AU - Aouada, D.
AU - Ottersten, B.
PY - 2019
SP - 573
EP - 582
DO - 10.5220/0007524405730582

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