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Computers to tag lost or suspicious people

Posted: 02 Jan 2009     Print Version  Bookmark and Share

Keywords:surveillance system  video panorama  behaviour patterns  aerial map 

Engineers are nearing the completion of a computerised surveillance system that will attempt to recognise whether a person on the street is acting suspiciously or appears to be lost. Intelligent video cameras, large video screens, and geo-referencing software are among the technologies that will soon be introduced to law enforcement and security agencies.

In the recent Proceedings of the 2008 IEEE Conference on Advanced Video and Signal Based Surveillance, James W. Davis and doctoral student Karthik Sankaranarayanan report that they've completed the first three phases of the project: they have one software algorithm that creates a wide-angle video panorama of a street scene, another that maps the panorama onto a high-resolution aerial image of the scene, and a method for actively tracking a selected target.

The ultimate goal is a networked system of "smart" video cameras that will let surveillance officers observe a wide area quickly and efficiently. Computers will carry much of the workload.

"In my lab, we've always tried to develop technologies that would improve officers' situational awareness, and now we want to give that same kind of awareness to computers," said Davis, an associate professor of computer science and engineering at Ohio State University.

The research isn't meant to gather specific information about individuals, he explained.

"In our research, we care what you do, not who you are. We aim to analyse and model the behaviour patterns of people and vehicles moving through the scene, rather than attempting to determine the identity of people. We are trying to automatically learn what typical activity patterns exist in the monitored area, and then have the system look for atypical patterns that may signal a person of interest—perhaps someone engaging in nefarious behaviour or a person in need of help."

The first piece of software expands the small field of view that traditional pan-tilt-zoom security cameras offer.

When surveillance operators look through one of these video cameras, they get only a tiny image—what some refer to as a "soda straw" view of the world. As they move the camera around, they can easily lose a sense of where they are looking within a larger context.

The Ohio State software takes a series of snapshots from every direction within a camera's field of view, and combines them into a seamless panorama.

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