Title :
Metro railway security algorithms with real world experience adapted to the RATP dataset
Author_Institution :
Vision Dept., SISELL, Gif-sur-Yvette, France
Abstract :
SISELL experimented during six month an underground railway intrusion detection system in a real metro environment in Lyon. Our algorithms have been adapted to fit the Lyon metro configuration, got improved and gained a real world experience. This article presents the implementation of these methods on the CREDS dataset.
Keywords :
image processing; object detection; railways; real-time systems; security; Lyon; RATP dataset; SISELL; challenge of real-time event detection solutions; image processing; metro railway security algorithms; underground railway intrusion detection system; Cameras; Data security; Extrapolation; Face detection; Filters; Intrusion detection; Motion analysis; Optical reflection; Rail transportation; Target tracking;
Conference_Titel :
Advanced Video and Signal Based Surveillance, 2005. AVSS 2005. IEEE Conference on
Print_ISBN :
0-7803-9385-6
DOI :
10.1109/AVSS.2005.1577263
