An affective inference model based on facial expression analysis

Abstract

Ubiquitous computing aims to reduce the complexity of interacting with computing devices. Analyzing psychological user states helps in this task. In this work we propose a computational model for analyzing psychological user states that takes into account three emotions that have not been explored deeply: interest, boredom and confusion. The model was constructed based on a video analysis of 35 engineering students during two class activities, all of whom reported the emotions they were feeling as they performed the activity. From the video, facial expressions features were extracted and matched with the emotion reported. This allowed us to construct patterns of facial expression and emotion inference rules. Our model is based on distances and indicators of change with respect to a user baseline, which allows the model to adapt to different users, moods and personal manners. Recognizing these emotions can be used as an implicit feedback in different systems. © Springer International Publishing 2013.