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Ingegneria Sismica

Ingegneria Sismica

Research on tennis serve drop prediction model based on attention mechanism

Author(s): Sheng Liu1, Yaxi Liu1, Xingying Liu1, Jiahao Hong1, Wenying Tian2
1Department of Physical Education, Jingdezhen Ceramic University, Jingdezhen, Jiangxi, 333403, China
2Department of Physical Education and Health, Dasheng Primary School, Ganzhou, Jiangxi, 342500, China
Liu, Sheng . et al “Research on tennis serve drop prediction model based on attention mechanism.” Ingegneria Sismica Volume 43 Issue 2: 1-18, doi:10.65102/is2026649.

Abstract

When the current method predicts the landing point of tennis serve, it does not analyze the force of tennis ball in the process of movement, which leads to the problem of low accuracy of the prediction results. Based on this, this study adopts the YOLOv4 motion target detection algorithm incorporating the attention mechanism to realize tennis ball target detection. At the same time, a three-dimensional coordinate reconstruction method of the tennis ball is designed, and a kinetic model of the tennis ball is established based on the force analysis, and a continuous model of the tennis ball kinematics is obtained by solving the kinetic differential equations, which is used for predicting the trajectory and calculating the landing point. The experimental results show that the incorporation of the attention mechanism improves the detection accuracy of the target detection algorithm. The prediction of the landing point position by the landing point prediction model designed in this paper is not much different from the actual landing point position. It shows that the model can be put into the daily training of tennis players to help them explore the technical and tactical laws of tennis matches, assist people in making technical and tactical decisions, and improve the scientificity of decision-making.

Keywords
Attention mechanism; YOLOv4; force analysis; serve drop prediction

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