Title: A recognition method of basketball players' shooting action based on Gaussian mapping

Authors: Zhu Xia

Addresses: The Engineering and Technical College of Chengdu University of Technology, Leshan 610041, China

Abstract: In order to overcome the problem of low recognition accuracy of traditional action recognition methods, this paper proposes a basketball player shooting action recognition method based on Gaussian mapping. Firstly, the basketball shooting image is preprocessed by block initialisation and denoising to improve the quality of the image. Secondly, based on the image preprocessing results, Gaussian mapping is used to extract the target features of shooting action image. Finally, according to the target characteristics, the multi-level feature decomposition and fuzzy processing of the image are carried out to realise the shooting action recognition. Experiments show that the designed method has high accuracy and recall rate, the maximum recognition accuracy reaches 96%, and the recognition time is short, and the number of false recognition frames is less, which shows that the designed method has high practical application performance.

Keywords: Gaussian mapping; basketball; shooting action; action recognition; feature extraction.

DOI: 10.1504/IJRIS.2023.130192

International Journal of Reasoning-based Intelligent Systems, 2023 Vol.15 No.2, pp.105 - 110

Received: 25 May 2022
Accepted: 07 Jul 2022
Published online: 06 Apr 2023 *

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