CSE 252 C Project Report Facial Attractiveness Scoring

The evaluation of attractiveness followed a scoring methodology rather than the usual classification one has not been attempted. This is desired for the sole reason that any person would be able to further decide between the attractiveness of two faces even if both are deemed attractive. In modelling this scenario, a continous scoring function is more appropriate. In this project, we implemented this scoring using Support Vector Machines to perform Regression on SIFT and Eigenfaces features extracted from the given data. The best results show a mean squared error of 0.082, which is considered promising in our case. With further refinement, such a tool will turn to be very useful in the hands of Internet dating services.