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Mathematicians Automate Gender Recognition

A University of Western Australia team of three computer scientists and two human anatomy experts has developed a mathematical model that matches the gender scores people give to human faces, ranging on a continuum from very masculine to very feminine.

Lead author of the PLOS One study, PhD student Syed Zulqarnain Gilani, said the model will be useful for quickly and accurately evaluating gender scores in research, such as investigating the relationship between masculinity and femininity and health, and in evaluating the success of cosmetic facial surgery.

“Until now the tool-of-choice for getting a gender score has been to call in subjects – sometimes as many as 300 per study – and to recruit raters to give each subject’s face a score,” he said. “Sometimes almost 700 raters might be needed for a study, giving as many as more than 22,000 ratings which then have to be evaluated. This is a very cumbersome and slow process.”

The team recruited 34 female and 30 male students aged about 20 and of different races, and invited 75 raters to give each of the 64 faces a gender score. Having analysed the scores, the team developed an algorithm that combines the two forms of distances: Euclidean (ruler) and geodesic (contours).

“Our results suggest that the human cognitive system employs a combination of Euclidean and geodesic distances between biologically significant landmarks of the face for gender scoring,” Syed said. “Our mathematical model is able to automatically assign an objective gender score to a 3D face with a correlation of up to 0.895 with the human subjective scores,” he said.