Recognition method of basketball players' throwing action based on image segmentation

Abstract

In order to solve the problems of low recognition accuracy and long recognition time in traditional basketball players' throwing action recognition methods, this paper proposes a new basketball players' throwing action recognition method based on image segmentation. The covariance matrix of noise data of basketball players' throwing action is constructed. The throwing action of basketball players is expressed by acceleration and angular velocity, and the acceleration vector of throwing action is obtained. The feature extraction of throwing action is completed by discrete Fourier transform algorithm. The image of basketball players' throwing action is segmented by threshold and edge, and the change features of throwing action are obtained by kernel function to complete the recognition of basketball players' throwing action. The experimental results show that the accuracy of the proposed method is about 98%, and the time cost is about 2.1 s.