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Authors: Ichraf Lahouli 1 ; Robby Haelterman 2 ; Zied Chtourou 3 ; Geert De Cubber 2 and Rabah Attia 4

Affiliations: 1 Royal Military Academy, Tunisia Polytechnic School and Military Academy of Tunisia, Belgium ; 2 Royal Military Academy, Belgium ; 3 Military Academy of Tunisia, Tunisia ; 4 Tunisia Polytechnic School, Tunisia

ISBN: 978-989-758-290-5

ISSN: 2184-4321

Keyword(s): Pedestrian Detection, Tracking, UAV, MPEG Motion Vectors, H.264.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Optical Flow and Motion Analyses ; Video Surveillance and Event Detection

Abstract: Video surveillance for security and intelligence purposes has been a precious tool as long as the technology has been available but is computationally heavy. In this paper, we present a fast and efficient framework for pedestrian detection and tracking using thermal images. It is designed for automatic surveillance applications in an outdoor environment like preventing border intrusions or attacks on sensitive facilities using image and video processing techniques implemented on-board Unmanned Aerial Vehicles (UAV)s. The proposed framework exploits raw H.264 compressed video streams with limited computational overhead. Our work is driven by the fact that Motion Vectors (MV) are an integral part of any video compression technique, by day and night capabilities of thermal sensors and the distinguished thermal signature of humans. Six different scenarios were carried out and filmed using a thermal camera in order to simulate suspicious events. The obtained results show the effectiveness of the proposed framework and its low computational requirements which make it adequate for on-board processing and real-time applications. (More)

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Paper citation in several formats:
Lahouli, I.; Haelterman, R.; Chtourou, Z.; De Cubber, G. and Attia, R. (2018). Pedestrian Detection and Tracking in Thermal Images from Aerial MPEG Videos. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-290-5 ISSN 2184-4321, pages 487-495. DOI: 10.5220/0006723704870495

@conference{visapp18,
author={Ichraf Lahouli. and Robby Haelterman. and Zied Chtourou. and Geert {De Cubber}. and Rabah Attia.},
title={Pedestrian Detection and Tracking in Thermal Images from Aerial MPEG Videos},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2018},
pages={487-495},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006723704870495},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Pedestrian Detection and Tracking in Thermal Images from Aerial MPEG Videos
SN - 978-989-758-290-5
IS - 2184-4321
AU - Lahouli, I.
AU - Haelterman, R.
AU - Chtourou, Z.
AU - De Cubber, G.
AU - Attia, R.
PY - 2018
SP - 487
EP - 495
DO - 10.5220/0006723704870495

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