In the last years, a new set of recommender systems has been recently developed to demonstrate the potential of emotion-based recommendations. Most of them are based on the acquisition and the analysis of data from micro blogging sites in order to predict the users' current emotional state. Considering that emotional aspects play a key role in culture heritage consumption, in this paper we present a facial emotion recognition approach in the context of cultural personalized recommendations. This work represents a first step for obtaining a cultural recommendation system capable to modulate users' emotions to make predictions.