Automatic Description Method for Sports Videos Based on Economic Management Effectiveness Visualization Techniques

Abstract

The automatic description (AD) of sports videos is a fundamental task for archiving the content of broadcasters, as well as understanding video scenes, and economic management effectiveness visualization techniques are key to the classification of sports videos. In this paper, a freestyle gymnastics video is used as an example to study the automatic video description by observing the set of movements of an athlete in a freestyle gymnastics video to generate the terminology of the movements performed by that athlete. The technique used in this paper to visualize the effectiveness of economic management is the long and short-term memory (LSTM) network model, which is used to learn the mapping relationship between word sequences and video frame sequences. Attention mechanisms (AM) are also introduced to highlight the importance of keyframes that determine freestyle gymnastics movements. The study is carried out by building a dataset of free gymnastics (FG) breakdown movements from professional events and applying a planned sampling method. Experimental results show that the method can improve the accuracy of an automatic free gymnastics video (FGV) description. The proposed method has a wide range of applications in sports analysis and instruction.