Inferring Emotional State from Facial Micro-Expressions

Personalized systems are becoming more and more popular in everyday life. Their goal is to adapt the output to the characteristics (i.e., interests and preferences) of the active user. To achieve this purpose, a process of inferring these characteristics is needed. In this paper, we verify the existence of some significant correlation between the facial micro-expressions of individuals and their emotional state. If so, we could think of monitoring the user while enjoying a certain visual stimulus, to understand her emotional response. For example, we could comprehend whether a visitor of a museum or an exhibition likes or dislikes the object she is observing, thus deriving her interests and tastes, regardless of the reality from which she comes. It could foster the role of the museum/exhibition intended as a vehicle of aggregation between a broad range of users, thus favoring their cultural and social inclusion. It could also allow us to design and realize recommender systems for enhancing the experience of users with difficulty in explicitly expressing their interests, such as people belonging to vulnerable groups (e.g., elderly, children, disabled people) or different cultures. Although the sample analyzed is limited and concerns a specific context (i.e., music video clips), the experimental results have been encouraging, thus spurring us to carry on with our research activities.