LAUSR

Game experience testing, an essential process for developing and servicing high-quality games, aims to evaluate and improve the play experience from the user perspective. Previous game experience tests are usually held offline with recruited test participants. Participants play the game in a controlled environment, and their experiences are recorded and analyzed by domain experts. However, this process not only requires substantial resources in terms of time and cost but also misses momentary data that can infer the user’s experience directly and quantitatively, such as facial expressions or body gestures of the participants while playing the game. In this paper, we propose a framework that can automatically collect and analyze video data of participants in a remote environment. We designed various experiments to verify that the proposed framework can automatically collect and analyze facial data in a remote environment. The experimental results show that our framework can be applied in gaming experience tests for popular commercial games currently in service. This paper presents a pioneering work that applies the face analysis method to the commercial game development process, and its purpose is beyond that of a pure research work.