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Neural Computation

March 2009, Vol. 21, No. 3, Pages 890-910
(doi: 10.1162/neco.2008.07-07-566)
© 2008 Massachusetts Institute of Technology
A Bi-Prototype Theory of Facial Attractiveness
Article PDF (1.27 MB)
Abstract

The attractiveness of human faces can be predicted with a high degree of accuracy if we represent the faces as feature vectors and compute their relative distances from two prototypes: the average of attractive faces and the average of unattractive faces. Moreover, the degree of attractiveness, defined in terms of the relative distance, exhibits a high degree of correlation with the average rating scores given by human assessors. These findings motivate a bi-prototype theory that relates facial attractiveness to the averages of attractive and unattractive faces rather than the average of all faces, as previously hypothesized by some researchers.