Analysis of the optimal shooting angle in football matches based on network data mining

Abstract

As an important research field in video understanding, human behavior recognition is widely used in intelligent monitoring, intelligent nursing, interactive behavior, and robot control. ObjectiveThe purpose of this study is to explore the analysis method of interaction behavior of soccer video. MethodsIn this study, we use scene simulation, big data analysis, experimental comparison, and other methods to analyze the interaction between players in a football video. The resultsof experiment and analysis of attack mode under interactive behavior show that the accuracy of attack direction determination results in traditional video analysis method and accurate analysis method is 75.60 % and 85.2 %, respectively. In this study, taking into account the two factors of staff proportion and average distance, the accuracy is improved to a certain extent, which can reach 91.5 %. It can be concluded that the deviation rate proposed in this study can better describe the position information of the football, can realize the detection of the basic attack mode, and can enable the computer to identify the attack direction of both players in the shortest time, which shows that the method is efficient and accurate. It provides a good analysis method for the research of human interaction behavior in football video and even in all kinds of videos.