Citation

Ting, Huong Yong and Sim, Kok Swee and Abas, Fazly Salleh (2014) Automatic badminton action recognition using RGB-D sensor. In: Advanced Materials Research. Trans Tech Publications, pp. 89-93. ISBN 978-303835284-6

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Abstract

This paper presents a method to recognize badminton action from depth map sequences acquired by Microsoft Kinect sensor. Badminton is one of Malaysia’s most popular, but there is still lack of research on action recognition focusing on this sport. In this research, bone orientation details of badminton players are computed and extracted in order to form a bag of quaternions feature vectors. After conversion to log-covariance matrix, the system is trained and the badminton actions are classified by a support vector machine classifier. Our experimental dataset of depth map sequences composed of 300 badminton action samples of 10 badminton actions performed by six badminton players. The dataset varies in terms of human body size, clothes, speed, and gender. Experimental result has shown that nearly 92% of average recognition accuracy (ARA) was achieved in inter-class leave one sample out cross validation test. At the same time, 86% of ARA was achieved in inter-class cross subject validation test.

Item Type:	Book Section
Additional Information:	Chapter 2: Artificial Intelligence and Data Mining, Data, Image and Signal Processing, Intelligent Automation and Control (3rd International Conference on Key Engineering Materials and Computer Science, KEMCS 2014; Singapore; Singapore; 5 August 2014 through 6 August 2014)
Subjects:	T Technology > T Technology (General) T Technology > TJ Mechanical Engineering and Machinery
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	23 Jan 2015 07:28
Last Modified:	23 Jan 2015 07:30
URII:	http://shdl.mmu.edu.my/id/eprint/5951

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