Group activity recognition based on deep learning:Overview and outlook
Group activity recognition has attracted much attention in the computer vision community,and it is widely applied in intelligent monitoring systems and sports video analysis.This paper provides a comprehensive review of the group activity recognition methods based on deep learning over the past seven years,which will help to promote the development of group activity recognition.First,the definition,the general recognition process,and the main challenges of group activity are introduced;Secondly,we classify the group activity recognition methods in modeling and internal mechanism,subdivide them,and further discuss the advantages and disadvantages of these methods;Thirdly,we present the common datasets of group activity recognition,the relevant open-source code libraries,and the evaluation index;Finally,we analyze the future research directions in group activity recognition.
group activity recognitiondeep learninghierarchical temporal modelinginteraction relationship reason-ingTransformer
国家科技期刊平台
NSTL
万方数据
