Accurate Recognition Method of Continuous Sports Action Based on Deep Learning Algorithm

Abstract

In order to improve the recognition effect of continuous sports action, an accurate recognition method of continuous sports action based on deep learning is proposed. The convolution neural network is used to predict the key points and center vector of human body in grid mode, and the key points of human body are grouped according to the distance from the key points of the human body to the center of human body, so as to obtain the sequence diagram of sports posture, input the posture sequence diagram of sports action in the deep learning network, and apply the best strategy of continuous action recognition obtained in the deep learning training stage to the accurate recognition of continuous sports action. The position of the rectangular frame of the attitude instead of the target attitude is predicted online by the convolution neural network, and the recognition is completed when the attitude stops. The experimental results show that this method can effectively recognize continuous sports actions in real time. The expected average overlap rate of different video attributes is high, which has better recognition effect. At different position error thresholds, it has high recognition accuracy.