Abstract
The task of real-time hand gesture recognition is extremely challenging due to a number of DOFs of hand pose and motion. However, for human-robot interaction in natural ways, gesture can provide a powerful interface tool for commanding a robot to perform a specific task. This paper presents a vision-based real-time gesture recognition system by segmenting the three largest skin color components and template-matching techniques with multiple features. Gesture commands are generated whenever the combinations of three skin-like regions at a particular image match with the predefined gestures. These gesture commands are sent to robots through a knowledge based software platform for human-robot interaction. The effectiveness of our method has been demonstrated by interacting with an entertainment robot named AIBO.
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Hasanuzzaman, M., Zhang, T., Ampornaramveth, V., Bhuiyan, M.A., Shirai, Y., Ueno, H. (2004). Gesture Recognition for Human-Robot Interaction Through a Knowledge Based Software Platform. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_66
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DOI: https://doi.org/10.1007/978-3-540-30125-7_66
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