A kinect based golf swing reorganization and segmentation system

Authors:
Lichao Zhang;Jui-Chien Hsieh;Shaozi Li
Affiliations:
Dept. Cognitive Science, Xiamen University, Xiamen, China, Dept. Information Management, Yuan-Ze University, Chung-Li, Taiwan;Dept. Information Management, Yuan-Ze University, Chung-Li, Taiwan;Dept. Cognitive Science, Xiamen University, Xiamen, China
Venue:
ICPCA/SWS'12 Proceedings of the 2012 international conference on Pervasive Computing and the Networked World
Year:
2012

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Abstract

This study displays a method to recognize and segment the time-sequential postures of golf swing. It's crucial to develop a system that can effectively recognize the steps of golf swing and facilitate self-learning of correct golf swing. First, a game controller, Kinect, is used to capture the 3D skeleton coordination of a golfer while performing swing. Second, a Hidden Markov Model (HMM) is applied onto the symbol sequence to recognize and segment the postures of golf swing. Results indicate that the proposed methods can effectively identify and categorize golf swing into 5 stages In conclusions, this developed golf swing training system is cost-effective as compared to traditional camera based golf swing trainer.