The feature vector is essentially a recipe for a face that can then be used to match it against others with similar feature vectors. However, it may be that with a given set of Eigenfaces, certain human faces produce very similar feature vectors. Hence, they are "average faces" that are hard for recognition systems to tell apart.
Systems that use Eigenfaces have another flaw which stems from the fact that they need to use the whole face as part of the recognition process. That means that it may be possible to successfully disguise your face against a recognition system simply by grinning or pulling some other face, according to Dr Jain - a strategy which would be unlikely to fool a real person.
Face to the floor
In addition, putting a scarf over the mouth and nose, or simply wearing dark glasses could fool the system. However, this is beginning to change, says Shengcai Liao, an assistant professor at the Center for Biometrics and Security Research in Beijing, China. He says new techniques are being developed that can use information from the nose or mouth alone if the eyes are occluded, or from the eyes and eyebrows if a scarf is covering the lower part of the face. "It's not possible to recognize a fully occluded face, but we can currently recognize faces with 30% or even 50% occlusion," he said. "We have even had success performing recognition from a mouth alone - something that it would be very difficult for a human to do."
But what about other countermeasures, such as those used by McAfee, which included skin darkening, facial distortion and colouring his hair?
Consider the use of shoe polish to change the colour of the skin. This would mute the intensity signature of a face, but light hitting the contours of the face would still produce an intensity signature that would allow for face detection, according to Dr Jain.
The distortion of the cheeks and nose would also have had little success. Research into the effects of nose jobs – or rhinoplasty - on facial recognition systems carried out by Dugelay show that it has little effect on recognition rates. (Ironically ,experimental facial recognition systems that use 3D imagery and which are generally more accurate than today's 2D systems are far more easily fooled by rhinoplasty, because it alters the shape of the face in three dimensions.)
Colouring the beard and hair would also have no effect, according to Alex Kilpatrick, a facial recognition researcher at Tactical Information Systems, a Texas-based biometric systems firm. "Changing your facial hair changes your appearance to a human dramatically whilst most computer systems are only interested in the area of your face from just above your eyebrows down to your chin, so hairstyles and colouring don't matter at all. You could grow a foot-long beard and it would make no difference," he said
However, there is a sure fire way to beat current systems, he says. Humans are rather good at recognizing people from almost angle, but one of facial recognition systems' key weaknesses is that they have a hard time detecting - let alone recognizing - a face if it is not looking towards the camera, according to Dr Kilpatrick. "Absolutely the easiest thing you can do is look down at your feet," he concluded. "That won't attract much attention, but because surveillance cameras are generally mounted high up or at least at eye level, it will defeat pretty much any recognition system."