The Emotracker: Visualizing Contents, Gaze and Emotions at a Glance

摘要

In the last years, Affective Computing investigations have focused the efforts in the automatic extraction of human emotions and in increasing the success rates in the emotion recognition task. However, there is a lack of automatic tools that intuitively visualize the users' emotional information. In this work, we propose Emotracker, a novel tool based on the combination of eye tracking and facial emotional recognition technologies that allows the visualization of contents, user emotions and gaze at a glance, and offers a wide range of visualization options, including emotional saccade maps and emotional heat maps. The simultaneous consideration of gaze and emotion opens the door to the evaluation of user engagement, which is of great importance for content creators, but has also other promising fields of application in psychology research and, more specifically, in autism.