Identifying illegal actions method of basketball players based on improved genetic algorithm
by Zhenyu Zhu
International Journal of Biometrics (IJBM), Vol. 16, No. 5, 2024

Abstract: In order to reduce the time required for identifying athlete violations and improve the recognition rate, this paper proposes a basketball player violation recognition method based on an improved genetic algorithm. Firstly, the surface electromyographic signals of athletes are collected using a wireless sEMG signal acquisition device. Secondly, the location of signal acquisition is determined and the time-domain features of the signal is extracted. Then, a composite filter is used to denoise the signal. Finally, the genetic algorithm is improved by combining support vector machines to design an action recognition classifier, which outputs the results of illegal action recognition through the recognition classifier. Through experiments, it can be seen that this method can effectively improve the recognition rate by 9.44%, and within 0.5 minutes, the recognition effect of basketball players' illegal actions is good.

Online publication date: Mon, 02-Sep-2024

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