A Novel Method for Predicting Facial Beauty Under Unconstrained Condition

Abstract

Facial beauty prediction is a challenging task in pattern recognition and biometric recognition as its indefinite evaluation criterion, compared with the other facial analysis task such as emotion recognition and gender classification. There are many methods designed for facial beauty prediction, whereas they have some limitations. Firstly, the results are almost achieved on a relative small-scale database, thus it is difficult to model the structure information for facial beauty. Secondly, most facial beauty prediction algorithm presented previously needs burdensome landmark or expensive optimization procedure. To this end, we establish a larger database and present a novel method to predict facial beauty. The works in this paper are notably superior to previous works in the following aspects: (1) A large database is established whose distribution is more reasonable and utilized in our experiments; (2) Both female and male facial beauty are analyzed under unconstrained conditions without landmark; (3) Multi-scale apparent features are learned by our method to represent facial beauty which is more expressive and requires less computation expenditure. Experimental results demonstrate the efficacy of the presented method from the aspect of accuracy and efficiency.