*Face recognition technology aids security - and look-alike searches*

    * James Randerson , science correspondent
    * The Guardian,
    * Friday January 25 2008

Scientists have developed a "face averaging" technique which
dramatically improves the success rate of computer face-recognition
systems and may be used to streamline airport security, solve crimes
captured on CCTV - and find celebrity lookalikes.

Using the new technique boosted the performance of a widely used face
recognition software package from 54% accuracy to 100%, University of
Glasgow researchers said yesterday in a paper published in Science.

The creator, Rob Jenkins, said the idea was based on the fact that
people are able to recognise familiar faces much better than new ones.
"If I just show you two photographs and say, 'is this the same person as
that?', we are actually pretty bad at that. We are actually much worse
than we think we are unless we are familiar with the face," he said.

However, we are much better at recognising the faces of people we know.
By making an average of 10 images of the same person his software is
able to eliminate variation from, for example, different lighting or
camera angles.

"These things affect the image a great deal but they don't tell you
anything about who it is," he said. "It is like you are extracting the
essence of that person's face."

Automatic systems would be very useful for recognising wanted criminals
automatically on CCTV or for making check-in at airports more
streamlined, but at present they typically make too many mistakes except
under very controlled conditions.

Jenkins and his colleague Professor Mike Burton tested the averaging
approach using FaceVACS, a system that is being tested at Sydney airport.

The website MyHeritage.com uses the software in a celebrity lookalike
service. Surfers submit images of themselves to the site, which matches
them to the nearest celebrity picture on its database of more than
31,000 photographs. Jenkins and Burton submitted images of 459
celebrities they knew were on the database. The system matched them to
the correct celebrity 54% of the time. When the pair created average
celebrity faces from 10 images and resubmitted them to the website, the
software was correct 100% of the time. "That's the first time anyone's
reported anything like that level of accuracy on such a variable set of
images," said Jenkins.

To make the test even tougher, they created averages using only those
images that the software had been unable to match in the first test. In
this test the software recognised the averaged faces correctly 80% of
the time. "We have fixed the baseline at zero, so any improvement we can
attribute just to the averaging process," he said.

Jenkins said his approach did not compete with current technology. "One
thing I really like about this approach is we are proposing a technique,
not a device," he said. "We are saying, you can keep the same machines,
but if you can change the input you can radically improve their
performance."