Emotional Facial Expressions Recognition & Classification

Human machine interaction is not as natural as interaction among humans. That is the reason why is not yet possible to completely substitute face-to-face communication by human-machine interaction in spite the theoretical feasibility of such a substitution in several professional areas including education and certain medical branches. To approach the naturalness of face-to-face interaction, machines should be able to emulate the way humans communicate with each other. Multi-media and man-machine communication systems could promote more efficient performance if machine understanding of facial expressions is improved. Based on this problematic issue, the current thesis is focused on the recognition of emotional facial expressions, finding interrelation between the facial expressions and labels and finally the classification of the expressions. One of the parts of this project is an emotional database which will contain images of faces, their corresponding Action Units and their labels. The contribution of this database to the problem stated above is that it can be used by systems in order to recognize emotional facial expressions given one of the database data i.e. action units’ combination. The other part of the project, which is an expert system for emotional classification, will enable to classify emotional expressions, the ones included in the database and all the possible combinations of them.