Automated Classification of Female Facial Beauty Using Learning Algorithms

Abstract

Among artists and psychologists, there exists a widespread belief that facial attractiveness can be measured by using mathematical ratios of facial features. Accordingly, in this paper we present an automated feature-based measuring system attempting to measure female facial beauty in a quantitative and repeatable way. The system is based on feature measurements made with image analysis algorithms and automated classification based on supervised learning. The system proves able to achieve good accuracy, substantially confirming the objective measurability of female facial beauty.