Crowd Behavior Monitoring and Analysis in Surveillance Applications: A Survey

Abstract

In the research field of computer vision, crowd monitoring and analyzing the behavior is an open topic for researchers due to its importance. Over the last decade many methodology has been proposed to do these task. These methodologies supposed to perform various tasks for the crowd which includes finding the strength of crowd in number for the proper crowd management in time or for the security reasons, prediction of future behavior of the crowd etc. Although many complex methodologies have been implemented for analyzing the crowd but there is still open scope for the methodologies which analyze the crowd in real-time, especially for the non-organized crowd. This paper presents a literature survey of the methodologies, proposed for the crowd monitoring and behavior analyzing for the both organized crowd and non-organized crowd. We also included the dataset details, used for those proposed methods with advantages and disadvantages. We included the methodologies based on traditional approaches as well as modern deep learning concept. We have a faith with a motive that this paper will help in the research community to understand about the various state of art methodologies used for crowd monitoring and analyzing.