Title: Identification of badminton players' swinging movements based on improved dense trajectory algorithm

Authors: Xue Jiang

Addresses: Public Teaching Department, Jilin Province Economic Management Cadre College, Changchun, 130012, China

Abstract: Badminton, as a fast and highly technical sport, requires high accuracy in identifying athletes' swing movements. Accurately identifying different swing movements is of great significance for technical analysis, coach guidance, and game evaluation. To improve the recognition accuracy of badminton players' swing movements, this text is based on an improved dense trajectory algorithm to improve the accuracy of recognising badminton players' swing movements. The features are efficiently extracted and encoded. The results on the KTH, UCF Sports, and Hollywood2 datasets demonstrated that the improved algorithm achieved recognition accuracy of 94.2%, 88.2%, and 58.3%, respectively. Compared to traditional methods, the innovation of research lies in optimised feature extraction methods, efficient algorithm design, and accurate action recognition. These results provide new ideas for the research and application of badminton swing motion recognition.

Keywords: badminton; swing recognition; dense trajectories; feature extraction; algorithm optimisation.

DOI: 10.1504/IJWET.2024.142213

International Journal of Web Engineering and Technology, 2024 Vol.19 No.3, pp.310 - 329

Received: 11 Mar 2024
Accepted: 04 Jun 2024
Published online: 14 Oct 2024 *

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