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FACE (AND IRIS) TIME
Savvides is also managing his charges toward the perfection of facial matching, essentially taking two-dimensional images--for example, newspaper photos or subway surveillance images--and translating them into three-dimensional computer models. Since criminals and terrorists are experts at evading detection, this system takes minimal facial characteristics and creates the three-dimensional model that can then be rotated to create a frontal posed two-dimensional image that is enrolled. The algorithm developed by Savvides' lab compares the information captured to the facial
| landmarks of thousands of faces stored in a database, and makes a more than educated guess at what the three-dimensional image should look like. The lab's work is filling a huge gap in facial recognition; most algorithms today necessitate a posed, illuminated image to be successful. Not very practical, Savvides says.
"These are very challenging problems," he says.
Savvides wouldn't confirm whether any of his lab's work is already in practical application, but reading between the lines, it's not a stretch to conclude that is the case. Labs such as this one are the heart of security research, and much of the work goes publicly unheralded. But it's invaluable to those entities chasing terrorists, or soldiers on the ground in Iraq and Afghanistan who were the early adopters of facial and iris recognition technologies.
Iris recognition is another primary calling of Savvides' lab. Researchers, for example, have equal number medical journals on their desks as technical tomes. Not only are they developing algorithms to pattern match iris characteristics, but they need to understand how diseases such as diabetes, cataracts and cancer affect iris modeling.
"Iris recognition is as unique as fingerprinting and more stable throughout a person's lifetime," Savvides says. "This allows you to identify individuals over diverse periods of time."
Acquisition of iris information is a primary thinking exercise at CyLab since most pattern-matching algorithms are mature and in use today. The difficulty in acquiring sufficient information lies in the fact that most surveillance cameras, for example, shoot from above, and the angles aren't conducive to proper enrollment, Savvides explains. A couple of years ago, the lab acquired a system called Sarnoff's Iris on the Move, a seven-foot tall portal similar to an airport metal detector. The system captures iris images while a subject walks through the portal. Unlike other capture systems, this one does not require a subject to stand still, pose and repeatedly adjust their glance into a scanner at a very close distance.
The system detects iris shape and characteristics on mobile subjects. While simultaneous detection and enrollment is not possible yet, the system is able to match captured information immediately with data stored on watchlist databases. In Iraq, for example, U.S. troops use portable iris enrollment and recognition devices; widespread use of the Sarnoff system would be useful should an insurgent make his way to U.S. soil and be stopped at the airport.
"We are very close," Savvides says. "This is extremely useful to law enforcement or in the fight against terrorism."
This was first published in November 2008