Smart CCTV learns to spot suspicious types

WHAT’S the difference between a suicide bomber and a cleaner? It sounds like the opening line of a sick joke, but for computer scientists working on intelligent video-surveillance software, being able to make that distinction is a key goal.

Current CCTV systems can collect masses of data, but little of it is used, says Shaogang Gong, a computer-vision computation researcher at Queen Mary, University of London. “What we really need are better ways to mine that data,” he says.

Gong is leading an international team of researchers to develop a next-generation CCTV system, called Samurai, which is capable of identifying and tracking individuals that act suspiciously in crowded public spaces. It uses algorithms to profile people’s behaviour, learning about how people usually behave in the environments where it is deployed. It can also take changes in lighting conditions into account, enabling it to track people as they move from one camera’s viewing field to another.

To improve the tracking of an individual at an airport, the system can also learn the routes people are likely to take – straight from the entrance to check-in, say. It can even follow a target as they move in a crowd, using the characteristic shape of the person, their luggage and the people they are walking with, to follow them as they walk between different camera views.

Samurai is designed to issue alerts when it detects behaviour that differs from the norm, and adjusts its reasoning based on feedback. So an operator might reassure the system that the person with a mop appearing to loiter in a busy thoroughfare is no threat. When another person with a mop exhibits similar behaviour, it will remember that this is not a situation that needs flagging up.

While video analysis tools already exist, they tend to operate according to rigid, predefined rules, says Gong, and cannot follow a large number of people across multiple cameras situated in busy public spaces.

The Samurai team last month demonstrated the system to commercial partners including BAA Airports in the UK. The researchers claim the prototype system successfully identified potential threats which may have been missed by human operators, using footage collected at Heathrow airport. The Samurai team has funding to continue refining their software until the end of 2011.

“The use of relevant feedback from human operators will be a very important part of these technologies,” says Paul Miller, of Queen’s University’s Centre for Secure Information Technologies in Belfast, UK, who is leading a project to develop a video-analysis system capable of predicting assaults on buses. “The key is developing learning algorithms that work not only in the lab but that are robust in real-world applications.”

http://www.newscientist.com/article/mg20427385.800-smart-cctv-learns-to-spot-suspicious-types.html

Popularity: 2% [?]