Other recognition systems are capable of producing three-dimensional
images, but most rely on two or more cameras.
And because each camera snaps the same photo from a different location, the resulting
images contain slight disparities in the location and color of pixels
that correspond to the same physical point on the person's face.
Identifying the pixels in each image that correspond to each other is
difficult, but necessary to create a three-dimensional image.
Photometric stereo overcomes the pixel-matching problem because one
camera takes multiple shots.
"Potentially, it could produce an excellent and cheap...system that would be very tough to beat simply because of the vast
amounts of 3D detail it captures. It's also non-contact and quick,"
said Michael Chantler of the School of Mathematical and
Computer Sciences at Heriot-Watt University in Edinburgh, Scotland.
The challenges, he said, will be in quickly comparing the captured image to others in a database as well as coping with variable facial expressions.
Petrou and her team hope to have a working prototype in three years.
