Intelligent Distributed Surveillance Systems

By Joe McCool

April 7, 2003

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Much of the European effort to develop intelligent surveillance stems from concerns with safety and efficiency on public transport. Closed-circuit television (CCTV) already plays a large part in airport terminals and metro stations. The general idea, then, is to capture video data from these cameras and program a computer to analyze it. A recent conference at the Institute of Electrical Engineers in London was dedicated to this task.

Francois Bremond from France's INRIA (Institut National de Recherche en Informatique et en Automatique) described a system they have developed for metros in Barcelona. According to Bremond, this is capable of detecting fighting, vandalism, blocking of exits, overcrowding and fraud (i.e. jumping over the ticket barrier).

It achieves all this by using a mixture of techniques from artificial intelligence: Bayesian Networks and AND/OR trees. Data frames from multiple cameras are combined to form 3D images. These are then scanned to identify semantic classes like PERSON, OCCLUDED PERSON, GROUP, CROWD, TRAIN, SCENE OBJECT and NOISE or UNKNOWN. A tracker module can identify different kinds of motion and hence behavior.

Recent tests on camera data from Brussels and Barcelona revealed 100 percent detection on fraud, vandalism, blocking and overcrowding. Fighting was detected 20 times out of 24. "The next step consists in designing the video interpretation system to be operational (able to cope with any unpredicted real world event) and working on a large scale," says Bremond.

Some, however, believe that there is a lot more to intelligent surveillance than at first seems obvious. "Even if we take a seemingly unambiguous problem such as overcrowding," says Christian Heath from King's College London, "we find no necessary correspondence between the density of passengers and its operational definition." Just because a camera indicates overcrowding, does not mean that the station is crowded.

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