Facial expression recognition is a hard and ambiguous problem in computer vision. It is hard due to the wide variety of faces and the wide variety of ways of representing the same expression. And it is ambiguous because, even though common approaches treat it as a classification problem, actually when looking at the same scene, different people can feel a different expression. In this presentation, we will show preliminary results obtained in an ongoing project of Discrete Choice Modeling of human perception of facial expressions. This new approach allows to exploit the mentioned heterogeneity of perceptions in a population of "experts" interpreting a facial expression, where an expert is somebody able to discern between different facial expressions, i.e. any human.