Research on application of athlete gesture tracking algorithms based on deep learning

It is difficult to track the posture of players in the course, mainly because of the changing environment and players. In this paper, the improved neural network is used to extract the trajectory characteristics of the athletes in the football player's game video, and the network is trained on a large number of data objects containing similarity objects, which improves the ability of the algorithm to distinguish the athlete's trajectory. A scheme of soccer attitude tracking based on twin neural network. The experimental results show that the algorithm has a good effect in the field of football and the accuracy is over 90% and the Siamese neural network is better than a traditional convolutional neural network.