Abstract
In this paper, we investigate on the relationship between player experience and body movements in a non-physical 3D computer game. During an experiment, the participants played a series of short game sessions and rated their experience while their body movements were tracked using a depth camera. The data collected was analysed and a neural network was trained to find the mapping between player body movements, player in- game behaviour and player experience. The results reveal that some aspects of player experience, such as anxiety or challenge, can be detected with high accuracy (up to 81%). Moreover, taking into account the playing context, the accuracy can be raised up to 86%. Following such a multi-modal approach, it is possible to estimate the player experience in a non-invasive fashion during the game and, based on this information, the game content could be adapted accordingly.
Original language | English |
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Title of host publication | Proceedings of the 2014 IEEE Conference on Computational Intelligence and Games |
Number of pages | 7 |
Publisher | IEEE Computer Society Press |
Publication date | 2014 |
Pages | 1-7 |
ISBN (Print) | 978-1-4799-3547-5, 978-1-4799-3546-8 |
DOIs | |
Publication status | Published - 2014 |
Event | IEEE Conference on Computational Intelligence and Games - Dortmund, Germany Duration: 26 Aug 2014 → 29 Aug 2014 |
Conference
Conference | IEEE Conference on Computational Intelligence and Games |
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Country/Territory | Germany |
City | Dortmund |
Period | 26/08/2014 → 29/08/2014 |