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Authors: Adel Saleh 1 ; Miguel Angel Garcia 2 ; Farhan Akram 1 ; Mohamed Abdel-Nasser 1 and Domenec Puig 1

Affiliations: 1 Rovira i Virgili University, Spain ; 2 Autonomous University of Madrid, Spain

ISBN: 978-989-758-175-5

Keyword(s): Activity Recognition, Kinematic Features, Classification.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Coding and Compression ; Image Formation and Preprocessing ; Motion, Tracking and Stereo Vision ; Video Surveillance and Event Detection

Abstract: This paper presents a video representation that exploits the properties of the trajectories of local descriptors in human action videos. We use spatial-temporal information, which is led by trajectories to extract kinematic properties: tangent vector, normal vector, bi-normal vector and curvature. The results show that the proposed method provides comparable results compared to the state-of-the-art methods. In turn, it outperforms compared methods in terms of time complexity.

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Paper citation in several formats:
Saleh, A.; Garcia, M.; Akram, F.; Abdel-Nasser, M. and Puig, D. (2016). Exploiting the Kinematic of the Trajectories of the Local Descriptors to Improve Human Action Recognition.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 180-185. DOI: 10.5220/0005781001800185

@conference{visapp16,
author={Adel Saleh. and Miguel Angel Garcia. and Farhan Akram. and Mohamed Abdel{-}Nasser. and Domenec Puig.},
title={Exploiting the Kinematic of the Trajectories of the Local Descriptors to Improve Human Action Recognition},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={180-185},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005781001800185},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Exploiting the Kinematic of the Trajectories of the Local Descriptors to Improve Human Action Recognition
SN - 978-989-758-175-5
AU - Saleh, A.
AU - Garcia, M.
AU - Akram, F.
AU - Abdel-Nasser, M.
AU - Puig, D.
PY - 2016
SP - 180
EP - 185
DO - 10.5220/0005781001800185

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