Recognition method of kicking and stride movements of Taekwondo athletes based on Gaussian mixture model

Autores/as

  • Tao Jia University of Political science and Law, Beijing, China

Palabras clave:

Gaussian mixture model; Taekwondo; Action recognition; Wavelet time domain feature

Resumen

In order to improve the accuracy of Taekwondo Athletes' motion recognition, a human motion recognition method based on Gaussian mixture model is proposed. This paper decomposes the structure of kicking and stride movement of human Taekwondo athletes to form a group of recognition targets, and investigates the changes of muscle surface under kicking and stride movement of Taekwondo athletes. The Gaussian mixture model is used to collect the shorttime feature images of kicking and stride movement of Taekwondo athletes, and the wavelet time-domain features of the images are obtained as the recognition vector space, The experimental results show that the method can effectively identify the movement characteristics and muscle changes of Taekwondo athletes, fully meet the research requirements.

Descargas

Publicado

2021-12-27

Cómo citar

Tao Jia. (2021). Recognition method of kicking and stride movements of Taekwondo athletes based on Gaussian mixture model . Revista De Psicología Del Deporte (Journal of Sport Psychology), 30(3), 315–323. Recuperado a partir de https://rpd-online.com/index.php/rpd/article/view/646