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According to Michael Bronstein, a computer scientist who works on 3-D face recognition at the Technion Institute of Technology, in Israel, another method used by commercial face-biometrics systems is to try to detect natural movements, such as blinking. However, these systems could be fooled by a video recording, Bronstein says.

Bigun’s approach takes the optical-flow concept a step further. “We looked at how a 3-D face moves,” he says. By comparing how bent photos of faces and real faces move, the researchers were able to identify differences in the trajectories of key facial points. For example, the movement of an ear and nose as a head turns slightly will be different from those appearing on a bent photo. This is because the parts of the face in the photo are still on a single plane, even if the photo is bent; conversely, the trajectories of 3-D facial features are more complex and follow a particular pattern relative to each other. Using this information, the researchers created a system to detect such discrepancies.

In experiments using 400 high-quality photographs and 400 video recordings of real people, the system was able to achieve an equal error rate–a common standard in biometrics in which the number of false matches is equal to the number of false rejections–of 0.5 percent. The results will be published in a forthcoming issue of the journal Image and Vision Computing.

“It makes sense to do this,” says Mark Nixon, a professor of computer vision at the University of Southampton, in the UK. “Liveness is quite an issue.” Some other kinds of biometrics already have ways of dealing with it, such as fingerprint biometrics. “You can use infrared and sweat to give a liveness measure,” Nixon says.

According to Bigun, the only way of beating the system he helped develop would be to make an accurate 3-D mask of someone’s face. While it’s feasible that someone with connections to Hollywood makeup artists could do this, it’s pretty unlikely, says Mitsubishi’s Jones. “It’s just not practical for the random criminal.”

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Credit: Klaus Kollreider, H. Fronthaler, Halmstad University

Tagged: Computing, optics, photography, facial recognition, Israel

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