A Seamless Modular Approach for Real-Time Video Analysis for Surveillance

desurmont, Xavier [Multitel] Bastide, Arnaud [Multitel] Delaigle, Jean-Francois [Multitel] Macq, Benoît [UCL]

In this paper we present a generic, flexible and robust approach for an intelligent real-time visual surveillance system. The proposed architecture integrates advanced video analysis tools, such as segmentation, tracking and events detection. The goal of these advanced tools is to provide help to operators by detecting events of interest in visual scenes. The approach is new because it is a seamless collaboration of many processing techniques from image space to dynamic scene space. We describe thoroughly an important section the vision system and prove its intrinsic modularity. The system is then demonstrated in an antiterrorist scenario of automatic detection of events in public facilities. A performance evaluation of the system is performed.