Security

Researchers Hone in on 'Spot-a-Terrorist' Spy Cams

Surveillance cameras today are only as good as their operators, who tend to fall back on the crude tools of profiling to pick suspicious individuals out of a crowd. Researchers at Ohio State University are at work on a network of "smart" surveillance cameras that can scan a crowd more efficiently. The concept involves stitching […]

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Surveillance cameras today are only as good as their operators, who tend to fall back on the crude tools of profiling to pick suspicious individuals out of a crowd. Researchers at Ohio State University are at work on a network of "smart" surveillance cameras that can scan a crowd more efficiently.

The concept involves stitching digital images together from the viewspace of a network of cameras, creating a 360-degree, "fish eye" view of a scene. Another piece of software creates an overhead map that can fix the ground coordinates of each pixel in the panorama; a third component would seamlessly track an individual as they move through the space. Science*Daily *has the scoop:

As a person walks across a scene, the computer can calculate exactly where the person is on the panorama and aerial map. That information can then be used to instruct a camera to follow him or her automatically using the camera’s pan-and-tilt control. With this system, it will be possible for the computer to 'hand-off' the tracking task between cameras as the person moves in and out of view of different cameras.

The next step for the researchers is developing an algorithm that can spot unusual behavior. This is a getting closer to the kind of "spot a terrorist" technology that military and homeland security types dream of creating. Not surprisingly, two of the undergrad researchers are being funded by the Air Force Research Lab. **

[PHOTO: Wikimedia]

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