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. © Springer-Verlag 2003.
CITATION STYLE
Kang, H., Lee, C. W., Jung, K., & Kim, H. J. (2004). A Clustering Approach to the Vision-Based Interface for Interactive Computer Games. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2690, 246–253. https://doi.org/10.1007/978-3-540-45080-1_33
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