Regularized single-kernel conditional density estimation for face description

This paper describes a single-kernel conditional density estimation system that obtains descriptive parameters including gender, age, ethnicity, pose and expression from images of faces. The method is able to do fast estimation of 39 parameters from live video, achieving accuracies comparable with alternatives that yield only a few parameters. The single-kernel model can be interrogated to examine the properties of parameters and the training regime and thus guide design of more complicated estimators.