Video content analytics is being increasingly employed for the security surveillance of mass-transit systems. The growing number of cameras, the presence of legacy networks, the limited bandwidth of wireless links, are some of the issues which highlight the importance of evaluating the performance of motion tracking against different levels of video compression. In this paper, we report the results of such an evaluation considering false-negative and false-positive metrics applied to videos captured from cameras installed in a real metro-railway environment. The evaluation methodology is based on the manual generation of the Ground Truth on selected videos at growing levels of MJPEG compression, and on its comparison with the Algorithm Result automatically generated by the Motion Tracker. The computation of reference performance metrics is automated by a tool developed in Matlab. Results are discussed with respect to the main causes of false detections, and hints are provided for further industrial applications.

Evaluating the Effects of MJPEG Compression on Motion Tracking in Metro Railway Surveillance / Cozzolino A; Flammini F; Galli V; Lamberti M; Poggi G; Pragliola C. - STAMPA. - 7517:(2012), pp. 142-154. (Intervento presentato al convegno ACIVS - Advanced Concepts for Intelligent Vision Systems 2012 tenutosi a Brno (Czech Republic) nel 4-7 September 2012) [10.1007/978-3-642-33140-4_13].

Evaluating the Effects of MJPEG Compression on Motion Tracking in Metro Railway Surveillance

Flammini F;
2012

Abstract

Video content analytics is being increasingly employed for the security surveillance of mass-transit systems. The growing number of cameras, the presence of legacy networks, the limited bandwidth of wireless links, are some of the issues which highlight the importance of evaluating the performance of motion tracking against different levels of video compression. In this paper, we report the results of such an evaluation considering false-negative and false-positive metrics applied to videos captured from cameras installed in a real metro-railway environment. The evaluation methodology is based on the manual generation of the Ground Truth on selected videos at growing levels of MJPEG compression, and on its comparison with the Algorithm Result automatically generated by the Motion Tracker. The computation of reference performance metrics is automated by a tool developed in Matlab. Results are discussed with respect to the main causes of false detections, and hints are provided for further industrial applications.
2012
Advanced Concepts for Intelligent Vision Systems: 14th International Conference, ACIVS 2012, Brno, Czech Republic, September 4-7, 2012, Proceedings
ACIVS - Advanced Concepts for Intelligent Vision Systems 2012
Brno (Czech Republic)
4-7 September 2012
Cozzolino A; Flammini F; Galli V; Lamberti M; Poggi G; Pragliola C
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1386661
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