Emotion Modelling and Facial Affect Recognition in Human-Computer and Human-Robot Interaction

Abstract

As research has revealed the deep role that emotion and emotion expression play in human social interaction, researchers in human-computer interaction have proposed that more effective human-computer interfaces can be realized if the interface models the user's emotion as well as expresses emotions. Affective computing was defined by Rosalind Picard (1997) as computing that relates to, arises from, or deliberately influences emotion or other affective phenomena. According to Picard's pioneering book, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, and even to have and express emotions. These positions have become the foundations of research in the area and have been investigated in great depth after their first postulation. Emotion is fundamental to human experience, influencing cognition, perception, and everyday tasks such as learning, communication, and even rational decision making. Affective computing aspires to bridge the gap that typical human-computer interaction largely ignored thus creating an often frustrating experience for people, in part because affect had been overlooked or hard to measure. In order to take these ideas a step further, towards the objectives of practical applications, we need to adapt methods of modelling affect to the requirements of particularshowcases. To do so, it is fundamental to review prevalent psychology theories on emotion, to disambiguate their terminology and identify the fitting computational models that can allow for affective interactions in the desired environments.