Affiliation:
1. De Montfort University, Leicester, UK
2. Departament d'Informàtica. Universitat de València, Burjassot, Spain
Abstract
Learning environments, among other user-centred applications, are excellent candidates to trial Computational Emotions and their algorithms to enhance user experience and to expand the system usability. However, this was not feasible because of the paucity in affordable consumer technologies that support the requirements of systems with advanced cognitive capabilities. Microsoft Kinect provides an accessible and affordable technology that can enable cognitive features such as facial expressions extraction and emotions detection. However, it comes with its own additional challenges, such as the limited number of extracted Animation Units (AUs). This paper presents a new approach that attempts at finding patterns of interaction between AUs, and between AUs and a given emotion. By doing so, the authors aim to reach a mechanism to generate a dynamically personified set of rules relating AUs and emotions. These rules will implicitly encode a person's individuality in expressing one's emotions.
Subject
Artificial Intelligence,Human-Computer Interaction,Software
Cited by
5 articles.
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1. Modulation Scheme for Biasing the Emotional Process of Autonomous Agents;Advances in Computational Intelligence and Robotics;2020
2. A Flexible Scheme to Model the Cognitive Influence on Emotions in Autonomous Agents;International Journal of Cognitive Informatics and Natural Intelligence;2018-10
3. The Cognitive Machine as Mental Language Automata;International Journal of Cognitive Informatics and Natural Intelligence;2018-01
4. SOM-Based Class Discovery for Emotion Detection Based on DEAP Dataset;International Journal of Software Science and Computational Intelligence;2018-01
5. Combining Supervised and Unsupervised Learning to Discover Emotional Classes;Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization;2017-07-09