Pedestrian Detection and Tracking in Thermal Images from Aerial MPEG Videos

Ichraf Lahouli, Robby Haelterman, Zied Chtourou, Geert De Cubber, Rabah Attia

2018

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.

Paper Citation

in Harvard Style

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 (VISIGRAPP 2018) - Volume 5: VISAPP; ISBN 978-989-758-290-5, SciTePress, pages 487-495. DOI: 10.5220/0006723704870495

in Bibtex Style

@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 (VISIGRAPP 2018) - Volume 5: VISAPP},
year={2018},
pages={487-495},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006723704870495},
isbn={978-989-758-290-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP
TI - Pedestrian Detection and Tracking in Thermal Images from Aerial MPEG Videos
SN - 978-989-758-290-5
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
PB - SciTePress