It presents a hybrid approach to estimate female facial beauty based on Machine Learning techniques. We use a combination of two approaches: Beauty Mask and Facial Proportions, to find the features that constitute Ideal Female facial beauty and thus, develop a female facial beauty scoring system based on the same. The dataset used in this work consists of 30 images being rated by 29 people. These are the front facial images of Winners, 1st Runner-up and 2nd Runner-up of Miss Universe Beauty Pageant from 2002 to 2011. Images are represented by a 50 element vector consisting of control points being selected manually with reference to the Beauty Mask. These points are used to calculate a total of 12 distances and 7 ratios for each image. These distances and ratios are also calculated for the Beauty Mask, and the final score is given on the basis of similarity between the respective ratios. A correlation of 67.78% shows the validity of our approach.
