Does your profile say it all? Using demographics to predict expressive head movement during gameplay

Abstract

In this work, we explore the relation between expressive head movement and user profile information in game play settings. Facial gesture analysis cues are statistically correlated with players' demographic characteristics in two different settings, during game-play and at events of special interest (when the player loses during game play). Experiments were conducted on the Siren database, which consists of 58 participants, playing a modified version of the Super Mario. Here, as player demographics are considered the gender and age, while the statistical importance of certain facial cues (other than typical/universal facial expressions) was analyzed. The proposed analysis aims at exploring the option of utilizing demographic characteristics as part of users' profiling scheme and interpreting visual behavior in a manner that takes into account those features.