Beauty may be in the eye of the beholder, but what if the beholder is a software program? Computer scientist Amit Kagian, at Tel Aviv University, believes he has successfully "taught" a computer how to interpret attractiveness in women. Writing in the journal Vision Research, Kagian explains that his software is a step towards developing artificial intelligence in computers. "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," says Kagian. "But our software lets a computer make an aesthetic judgment. Linked to sentiments and abstract thought processes, humans can make a judgment, but they usually don't understand how they arrived at their conclusions."
To create his software, Kagian used a panel of humans who were asked to rate the attractiveness of 100 different female Caucasian faces. The subjects rated the images on a scale of 1 through 7 and did not explain why they chose their 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 color were fed into the analysis as well. Based on human preferences, the machine "learned" the relation between facial features and attractiveness scores and was then put to the test on a fresh set of faces. "The computer produced impressive results - its rankings were very similar to the rankings people gave," said Kagian, adding that it was as though the computer "learned" implicitly how to interpret beauty through processing previous data it had received.
The notion that beauty can be boiled down to a mathematical model was first mooted 2,000 years ago by the Greek philosopher and mathematician Pythagoras, who observed the connection between math, geometry and beauty.
Kagian thinks Pythagoras was on the right track. "Personally, I believe that some kind of universal correctness to beauty exists in nature, an aesthetic interpretation of the universal truth. But because each of us is trapped with our own human biases and personalized viewpoints, this may detract us from finding the ultimate formula to a complete understanding of beauty."
Kagian says that a possible next step is to teach computers how to recognize "beauty" in men. This may be more difficult, he notes, as psychological research has shown that there is less agreement as to what defines "male beauty" among human subjects.
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Source: Tel Aviv University
