Learning group interaction for sports video understanding from a perspective of athlete  

作　　者：Rui HE Zehua FU Qingjie LIU Yunhong WANG Xunxun CHEN 

机构地区：[1]Intelligent Recognition and Image Processing(IRIP)Lab,School of Computer Science and Engineering,Beihang University,Beijing 100191,China [2]Hangzhou Innovation Institute,Behang University,Hangzhou 310051,China [3]National Computer Network Emergency Response Technical Team/Coordination Center of China(CNCERT or CNCERT/CC),Beijing 100029,China

出　　处：《Frontiers of Computer Science》2024年第4期175-188,共14页中国计算机科学前沿（英文版）

基　　金：National Natural Science Foundation of China(Grant No.U20B2069);Fundamental Research Funds for the Central Universities.

摘　　要：Learning activities interactions between small groups is a key step in understanding team sports videos.Recent research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than the athlete.For team sports videos such as volleyball and basketball videos,there are plenty of intra-team and inter-team relations.In this paper,a new task named Group Scene Graph Generation is introduced to better understand intra-team relations and inter-team relations in sports videos.To tackle this problem,a novel Hierarchical Relation Network is proposed.After all players in a video are finely divided into two teams,the feature of the two teams’activities and interactions will be enhanced by Graph Convolutional Networks,which are finally recognized to generate Group Scene Graph.For evaluation,built on Volleyball dataset with additional 9660 team activity labels,a Volleyball+dataset is proposed.A baseline is set for better comparison and our experimental results demonstrate the effectiveness of our method.Moreover,the idea of our method can be directly utilized in another video-based task,Group Activity Recognition.Experiments show the priority of our method and display the link between the two tasks.Finally,from the athlete’s view,we elaborately present an interpretation that shows how to utilize Group Scene Graph to analyze teams’activities and provide professional gaming suggestions.

关 键 词：group scene graph group activity recognition scene graph generation graph convolutional network sports video understanding 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN912.3[自动化与计算机技术—计算机科学与技术]