Title: The method of table tennis players' posture recognition based on a genetic algorithm

Authors: Jiesen Yin

Addresses: Department of Sports, Wuxi Institute of Technology, Wuxi, Jiangsu, 214121, China

Abstract: In order to overcome the problems of poor denoising effect, low recognition efficiency and low recognition accuracy of the existing methods of table tennis players' posture recognition, this paper proposes a method of table tennis players' posture recognition based on a genetic algorithm. The optimisation model of multi-objective key frame extraction is constructed, and the optimisation model of multi-objective key frame extraction is solved by genetic algorithm to obtain the key frame. Kalman filter is used to remove the noise in the key frame, eliminate the interference of the noise on the recognition result, and shorten the recognition time. According to the results of noise removal, the dynamic time warping algorithm is used to recognise table tennis players' posture. The experimental results show that the proposed method has good denoising effect, high recognition efficiency and high recognition accuracy, with the highest recognition accuracy of 98.7%.

Keywords: genetic algorithm; table tennis; athletes; pose recognition; key frame extraction.

DOI: 10.1504/IJBM.2021.114652

International Journal of Biometrics, 2021 Vol.13 No.2/3, pp.243 - 257

Received: 07 Apr 2020
Accepted: 09 Jun 2020
Published online: 29 Apr 2021 *

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