23-08-2012, 02:59 PM
Neural Network Based Video Surveillance System
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Abstract
Video surveillance systems are usually composed of a
network of active video sensors that continuously capture the
scenes and present them to a human operator for analysis and
event detection. Unfortunately human operators are often unable
to monitor the video streams coming from a large number of video
sensors.
In this paper a semantic event detection system based on a neural
classifier is presented to screen continuous video streams and
detect relevant events, specifically for video surveillance. The
goal of the proposed system is to automatically collect real-time
information to improve the awareness of security personnel and
decision makers.
Our research is focused on the use of the “known scene