UvA-DARE (Digital Academic Repository) Towards Personalised Gaming via Facial Expression Recognition Towards Personalised Gaming via Facial Expression Recognition

In this paper we propose an approach for personalising the space in which a game is played (i.e., levels) dependent on classifications of the user’s facial expression – to the end of tailoring the affective game experience to the individual user. Our approach is aimed at online game personalisation, i.e., the game experience is personalised during actual play of the game. A key insight of this pa- per is that game personalisation techniques can leverage novel computer vision-based techniques to unobtrusively infer player experiences automatically based on facial expression analysis . Specifically, to the end of tailoring the affective game experience to the individual user, in this paper we (1) leverage the proven I N S IGHT facial expres- sion recognition SDK as a model of the user’s affective state (Sightcorp 2014), and (2) employ this model for guiding the online game personalisation process. User studies that validate the game personalisation approach in the actual video game I NFINITE M ARIO B ROS . re-veal that it provides an effective basis for converging to an appropriate affective state for the individual human player.