Carnegie Mellon’s CyLab wins Edison award

Carnegie Mellon University's CyLab Biometrics Center has been awarded a gold Edison Award in the Diagnostic/Detection Systems category for its Unconstrained Biometric Identification platform.CyLab says the UBI platform can enhance and identify people from very low resolution footage that includes facial occlusions, even when not looking directly at the camera. It can also acquire high resolution eye images from up to 12 meters away and identify people based solely on their iris patterns.”It is a huge honor for our lab to receive an Edison Award,” said Marios Savvides, research professor of electrical and computer engineering and founder and director of the Biometrics Center told the Carnegie Mellon News. “This award is an important verification of our technological innovations and their positive impact on society.”The centre recently demonstrated a video that showed its long-range iris system revealing a driver's identity by scanning their iris through a car's side mirror.”Savvides' lab is creating opportunities to save lives by enabling officers to identify potentially dangerous criminals without even approaching the vehicle,” said Jim Garrett, dean of Carnegie Mellon's College of Engineering.The center also addresses the problem of partially-occluded faces in photographs, such as when a subject's face is not directly facing the camera and only part of a subject's face is captured. Savvides' technology is able to predict what the subject's face looks like in its entirety with high accuracy, even with a blurry, low-resolution image.”The computer is doing something the human brain cannot do,” Savvides said. “I just find it extremely fascinating how machine learning and pattern-recognition can create this artificial intelligence system that can make correct inferences from such small amounts of facial data.”

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