Recognition of human action for game system

Authors:
Hye Sun Park;Eun Yi Kim;Sang Su Jang;Hang Joon Kim
Affiliations:
Department of Computer Engineering, Kyungpook National Univ, Korea;Department of Internet and Multimedia Engineering, Konkuk Univ, Korea;Department of Computer Engineering, Kyungpook National Univ, Korea;Department of Computer Engineering, Kyungpook National Univ, Korea
Venue:
AIS'04 Proceedings of the 13th international conference on AI, Simulation, and Planning in High Autonomy Systems
Year:
2004

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Abstract

Using human action, playing a computer game can be more intuitive and interesting. In this paper, we present a game system that can be operated using a human action. For recognizing the human actions, the proposed system uses a Hidden Markov Model (HMM). To assess the validity of the proposed system we applied to a real game, Quake II. The experimental results verify the feasibility and validity of this game system.This system is currently capable of recognizing 13 gestures, corresponding to 20 keyboard and mouse commands for Quake II game.