Non-intrusive Measurement of Player Engagement and Emotions - Real-Time Deep Neural Network Analysis of Facial Expressions During Game Play
| Autor: | Henrik Schoenau-Fog, Dines Rae Selvig |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Facial expression
Erikson's stages of psychosocial development 020207 software engineering Conation 02 engineering and technology Game play Correlation Continuation Two-player game 0202 electrical engineering electronic engineering information engineering Player engagement 020201 artificial intelligence & image processing Psychology Cognitive psychology |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030501631 HCI (31) |
| Popis: | Prior research suggests and reveals that there is a correlation between human emotional responses and the subjective qualities of digital interactive experiences. Using facial analysis done by deep neural networks presents a true non-intrusive way of measuring emotional responses and engagement assessed as the desire to continue playing. This paper proposes a tool to measure emotional responses across eight different emotions and in real time of any game. The emotional recognition system achieves an accuracy of 98% and the continuation desire system achieves 93.3% accuracy in a pilot test with a two player game and 78.5% accuracy in a single player game. This forms a strong tool that shows a correlation between emotions and the continuation desire of a player, which can be used to evaluate engagement in games and digital interactive experiences, e.g. in critical stages of development of said content. |
| Databáze: | OpenAIRE |
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