A framework for investigating the use of face features to identify naturally generated emotion
Facial expression recognition, Face biometrics, Emotion analysis, Action units.
Emotion-based analysis has raised a lot of interest particularly in areas such as forensics, medicine, psychology and human-machine interface. Following this trend, the use of facial analysis (either automatic or human-based) is the most common subject to be investigated once this type of data can easily be collected and is well accepted to the general population. Despite this popularity, due to several constraints found in real world scenarios (e.g. lightning, complex backgrounds, facial hair and so on), automatically predicting affective information from face accurately can be very challenging. This paper presents a framework which aims to analyse emotional experiences through naturally generated facial expressions. Our main contribution is a new 4-dimensional model to describe emotional experiences in terms of appraisal, facial expressions, mood and subjective experiences. In addition, we propose a new protocol to obtain spontaneous emotional reactions and an experiment in order to evaluate the proposed method. The results have shown that emotional states were observed in most participants, thus showing the efficiency of the proposed methodology. Moreover, our results pointed out that spontaneous facial reactions to emotions are very different from those in prototypic expressions due to their lack of expressiveness.