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A Literature Review on Video Analytics of Crowded Scenes

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Intelligent Multimedia Surveillance

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.

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Authors and Affiliations

  1. ZWEEC Analytics, Singapore, Singapore

    Myo Thida & How-lung Eng

  2. Kingston University, London, UK

    Yoke Leng Yong, Pau Climent-Pérez & Paolo Remagnino

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  1. Myo Thida
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  2. Yoke Leng Yong
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  3. Pau Climent-Pérez
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  4. How-lung Eng
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  5. Paolo Remagnino
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Correspondence to Myo Thida .

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Editors and Affiliations

  1. Department of Applied Computer Science, University of Winnipeg, Winnipeg, Canada

    Pradeep K. Atrey

  2. Dept. of Computer Science, National University of Singapore, Singapore, Singapore

    Mohan S. Kankanhalli

  3. Elec. Engineering and Computer Science, Queen Mary University of London, London, United Kingdom

    Andrea Cavallaro

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Thida, M., Yong, Y.L., Climent-Pérez, P., Eng, Hl., Remagnino, P. (2013). A Literature Review on Video Analytics of Crowded Scenes. In: Atrey, P., Kankanhalli, M., Cavallaro, A. (eds) Intelligent Multimedia Surveillance. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41512-8_2

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