By Christopher Shea Face-recognition technology is crossing a
new threshold: identifying people even after they’ve had plastic
surgery. Current algorithms that take a “holistic” approach to
analyzing faces are extraordinarily accurate, but they can be
thrown off by facelifts, new noses, and bee-stung lips. But
working on the theory that small regions of the face would be
less altered by surgery than overall facial proportions,
researchers at the University of Notre Dame created a system
that begins by breaking faces down into constituent parts. The
faces tested were part of a database of some 1,800 “before” and
“after” shots of plastic-surgery patients — which caused
additional challenges. Cutting-edge face-recognition relies on
multiple images of a person, to account for different
photographic angles and lighting. But multiple “before” images
weren’t available in this case. Instead, researchers instructed
the computer to mine a database of thousands of random faces to
locate chins, eyes, and eyebrows that cl