Computer gauges attractive quotient
Here is how Indo-Israeli Amit Kagian successfully "taught" a computer to recognise attractiveness in women on a ranking scale.Updated: Apr 05, 2008 20:18 IST
Beauty indeed lies in the eye of the beholder - but does the beholder have to be human? Apparently not. According to a paper in the journal Vision Research, Indo-Israeli Amit Kagian successfully "taught" a computer to recognise attractiveness in women.
"The computer produced impressive results. Its rankings were very similar to the rankings people gave," said Kagian of Tel Aviv University.
This is a remarkable achievement, Kagian added, because it's as though the computer "learned" implicitly how to interpret beauty through processing previous data it had received.
But there's a more serious dimension to this issue that goes beyond mere vanity. It is a step towards developing artificial intelligence, said Kagian.
Other applications for the software could be in plastic and reconstructive surgery and computer visualisation programmes such as face-recognition technologies.
"Until now, computers have been taught how to identify basic facial characteristics, such as the difference between a woman and a man, and even to detect facial expressions," said Kagian.
"But our software lets a computer make an aesthetic judgement. Linked to sentiments and abstract thought processes, humans can make a judgement, but they usually don't understand how they arrived at their conclusions."
In the first step of the study, 30 men and women were presented with 100 different faces of Caucasian women, roughly of the same age, and were asked to judge the beauty of each face.
The subjects rated the images on a scale of 1 through 7 and did not explain why they chose certain scores.
Kagian and his colleagues then went to the computer and processed and mapped the geometric shape of facial features mathematically. Additional features such as face symmetry, smoothness of the skin and hair colour was fed into the analysis as well.
Based on human preferences, the machine "learned" the relation between facial features and attractiveness scores and then used that to "rate" a fresh set of faces.