Abstract
In interactive computer games, vision can be a powerful interface between humans and computers. In this paper, we propose a vision-based interface for 3D action games. We make dynamic gestures to input of the interface and represent a user’s gesture as an ordered sequence of a user’s poses. To estimate a human poses, we classify whole frames using K-Means clustering. For recognizing a gesture, each symbols from input sequence is matched with templates composed of ordered pose symbol sequences that indicate the specific gestures. Our interface recognizes ten gesture commands with a single commercial camera and no markers. Experimental results with 50 humans show an average recognition rate of 93.72 % per a gesture command.
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Kang, H., Lee, C.W., Jung, K., Kim, H.J. (2003). A Clustering Approach to the Vision-Based Interface for Interactive Computer Games. In: Liu, J., Cheung, Ym., Yin, H. (eds) Intelligent Data Engineering and Automated Learning. IDEAL 2003. Lecture Notes in Computer Science, vol 2690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45080-1_33
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DOI: https://doi.org/10.1007/978-3-540-45080-1_33
Publisher Name: Springer, Berlin, Heidelberg
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