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Automated analysis of facial cues from videos as a potential method for differentiating stress and boredom of players in games
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Federal University of Fronteira Sul, Chapecó, Brazil. (Interaction Lab)ORCID iD: 0000-0001-6479-4856
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Interaction Lab)ORCID iD: 0000-0002-9972-4716
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Interaction Lab)ORCID iD: 0000-0001-9287-9507
2018 (English)In: International Journal of Computer Games Technology, ISSN 1687-7047, E-ISSN 1687-7055, article id 8734540Article in journal (Refereed) Published
Abstract [en]

Facial analysis is a promising approach to detect emotions of players unobtrusively, however approaches are commonly evaluated in contexts not related to games, or facial cues are derived from models not designed for analysis of emotions during interactions with games. We present a method for automated analysis of facial cues from videos as a potential tool for detecting stress and boredom of players behaving naturally while playing games. Computer vision is used to automatically and unobtrusively extract 7 facial features aimed to detect the activity of a set of facial muscles. Features are mainly based on the Euclidean distance of facial landmarks and do not rely on pre-dened facial expressions, training of a model or the use of facial standards. An empirical evaluation was conducted on video recordings of an experiment involving games as emotion elicitation sources. Results show statistically signicant dierences in the values of facial features during boring and stressful periods of gameplay for 5 of the 7 features. We believe our approach is more user-tailored, convenient and better suited for contexts involving games.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2018. article id 8734540
Keywords [en]
games, boredom, stress, facial expression, affective computing, computer vision
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-14771DOI: 10.1155/2018/8734540ISI: 000427897600001Scopus ID: 2-s2.0-85046279378OAI: oai:DiVA.org:his-14771DiVA, id: diva2:1185225
Funder
EU, European Research Council, Project Game Hub ScandinaviaAvailable from: 2018-02-23 Created: 2018-02-23 Last updated: 2018-05-17Bibliographically approved

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Bevilacqua, FernandoEngström, HenrikBacklund, Per

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