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Local Tech Wire

CHAPEL HILL, N.C. – experts in informatics and computational performance will work with Cambridge Intelligent Systems (CIS) in Raleigh to improve biometric systems used by the U.S. Department of Homeland Security (DHS) to track and identify suspected terrorists as they enter and leave the U.S.

The project, funded by the , a Research Triangle Park-based collaboration involving , , the and the , provides $200,000 to RENCI and CIS to research next generation biometric systems that can reliably identify people of interest under challenging, real-world conditions.

"Biometric technologies currently used by DHS and others operate very well with stationary, cooperative subjects in a controlled environment," said Charles Schmitt, director of RENCI’s informatics division and principal investigator for the project.

"Fingerprint, iris, and face recognition all have very high recognition rates under these conditions, but the big unsolved problem is how to identify people in surveillance-like video,” added Schmitt. “Identifying a person who is moving, uncooperative or a long distance from the surveillance system is a very challenging problem – one that homeland security officials are extremely interested in solving."

Land-based border crossings are among the most difficult environments for biometric identification systems. Ideally, DHS wants the ability to identify people crossing the borders in cars and on foot without having to stop every individual or car.

"To do that, you need a robust, multi-modal, video-based biometric system," explained Schmitt. "It has to be video-based because it has to be opportunistic; you never know when you’ll get a good look at someone’s face or iris."

During phase one of the project, RENCI and CIS will define the requirements for a land-border-exit biometric system, evaluate a wide array of existing and near-future biometric technologies against those requirements, and develop architecture for deploying the best technologies for day-to-day use by the DHS.

The team will evaluate data-capture challenges, including how close video cameras can be placed to subjects and at what angles, how people tend to cross the border (car, foot, motorcycle, public transit), environmental factors (ambient noise, traffic congestion, and numbers of vehicles with tinted windows), and whether the site has access to electricity and the Internet.

From that data the team will produce a report to DHS that outlines basic requirements for reliable video-based, multi-modal biometric identification systems that evaluates specific biometric identification modes.

As part of this work, RENCI and CIS will create a reference biometric architecture for use at border crossings and will evaluate leading video identification technologies to determine the gap between current capabilities and DHS needs.

The Institute for Homeland Security Solutions is a research consortium established to conduct applied research in the social and behavioral sciences to address a wide range of homeland security challenges.

Founded as a major collaboration involving UNC Chapel Hill, Duke University and North Carolina State University, RENCI is a statewide organization based at UNC-Chapel Hill with facilities at campuses across North Carolina.