A literature review on video analytics of crowded scenes

Abstract

This chapter presents a review and systematic comparison of the state of the art on crowd video analysis. The rationale of our review is justified by a recent increase in intelligent video surveillance algorithms capable of analysing automatically visual streams of very crowded and cluttered scenes, such as those of airport concourses, railway stations, shopping malls and the like. Since the safety and security of potentially very crowded public spaces have become a priority, computer vision researchers have focused their research on intelligent solutions. The aim of this chapter is to propose a critical review of existing literature pertaining to the automatic analysis of complex and crowded scenes. The literature is divided into two broad categories: the macroscopic and the microscopic modelling approach. The effort is meant to provide a reference point for all computer vision practitioners currently working on crowd analysis. We discuss the merits and weaknesses of various approaches for each topic and provide a recommendation on how existing methods can be improved.