This is a great read. The OpenCV part hit a bit too close to home though: I was stuck for a minute trying to think how he managed to segment faces well enough to compute ratios (not just as a rectangle or a blob) given all of the possible conditions/perspectives of the photos.
you bet! i was automatically thinking about how did he manage to get sufficiently good resolution, how did he cope with lighting/background changes, and so on....
It's really the wrong approach. Supervised learning is the way to go. For example a paper by Kumar et al.[1] shows how to build an "attractive woman" classifier that is 83% accurate.
