Abstract
In this paper, we propose gesture recognition in multiple people environment. Our system is divided into two modules: Segmentation and Recognition. In segmentation part, we extract foreground area from input image, and we decide the closest person as a recognition subject. In recognition part, firstly we extract feature point of subject’s both hands using contour based method and skin based method. Extracted points are tracked using Kalman filter. We use trajectories of both hands for recognizing gesture. In this paper, we use the simple queue matching method as a recognition method. We also apply our system as an animation system. Our method can select subject effectively and recognize gesture in multiple people environment. Therefore, proposed method can be used for real world application such as home appliance and humanoid robot.
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Hong, Sj., Setiawan, N.A., Lee, Cw. (2007). Real-Time Vision Based Gesture Recognition for Human-Robot Interaction. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_61
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DOI: https://doi.org/10.1007/978-3-540-74819-9_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
Online ISBN: 978-3-540-74819-9
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