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
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.
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