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Bro-cam: Improving Game Experience with Empathic Feedback Using Posture Tracking

  • Chiew Seng Sean Tan
  • Johannes Schöning
  • Jan Schneider Barnes
  • Kris Luyten
  • Karin Coninx
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7822)

Abstract

In todays videogames user feedback is often provided through raw statistics and scoreboards. We envision that incorporating empathic feedback matching the player’s current mood will improve the overall gaming experience. In this paper we present Bro-cam, a novel system that provides empathic feedback to the player based on their body postures. Different body postures of the players are used as an indicator for their openness. From their level of openness, Bro-cam profiles the players into different personality types ranging from introvert to extrovert. Empathic feedback is then automatically generated and matched to their preferences for certain humoristic feedback statements. We use a depth camera to track the player’s body postures and movements during the game and analyze these to provide customized feedback. We conducted a user study involving 32 players to investigate their subjective assessment on the empathic game feedback. Semi-structured interviews reveal that participants were positive about the empathic feedback and Bro-cam significantly improves their game experience.

Keywords

Affective State Personality Type Game Experience Kinect Sensor Depth Camera 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chiew Seng Sean Tan
    • 1
  • Johannes Schöning
    • 1
  • Jan Schneider Barnes
    • 1
  • Kris Luyten
    • 1
  • Karin Coninx
    • 1
  1. 1.tUL – iMinds Expertise Centre for Digital MediaHasselt UniversityDiepenbeekBelgium

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