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http://dx.doi.org/10.5302/J.ICROS.2015.14.0078

Analysis of Table Tennis Swing using Action Recognition  

Heo, Geon (Graduate School of Automotive Engineering, Seoul National University of Science and Technology)
Ha, Jong-Eun (Department of Mechanical and Automotive Engineering, Seoul National University of Science and Technology)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.21, no.1, 2015 , pp. 40-45 More about this Journal
Abstract
In this paper, we present an algorithm for the analysis of poses while playing table-tennis using action recognition. We use Kinect as the 3D sensor and 3D skeleton data provided by Kinect for further processing. We adopt a spherical coordinate system and feature selected using k-means clustering. We automatically detect the starting and ending frame and discriminate the action of table-tennis into two groups of forehand and backhand swing. Each swing is modeled using HMM(Hidden Markov Model) and we used a dataset composed of 200 sequences from two players. We can discriminate two types of table tennis swing in real-time. Also, it can provide analysis according to similarities found in good poses.
Keywords
action recognition; Kinect; k-means clustering; HMM (Hidden Markov Model);
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Times Cited By KSCI : 1  (Citation Analysis)
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