Title: Crowd detection and counting using a static and dynamic platform: state of the art

Authors: Huma Chaudhry; Mohd Shafry Mohd Rahim; Tanzila Saba; Amjad Rehman

Addresses: Faculty of Computing, Universiti Teknologi Malaysia, Skudai Johor, 81310, Malaysia ' UTM-IRDA Digital Media Centre, Faculty of Computing, Universiti Teknologi Malaysia, Skudai Johor, 81310, Malaysia ' College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia ' College of Computer and Information Systems, Al Yamamah University, Riyadh, 11512, Saudi Arabia

Abstract: Automated object detection and crowd density estimation are popular and important area in visual surveillance research. The last decades witnessed many significant research in this field however, it is still a challenging problem for automatic visual surveillance. The ever increase in research of the field of crowd dynamics and crowd motion necessitates a detailed and updated survey of different techniques and trends in this field. This paper presents a survey on crowd detection and crowd density estimation from moving platform and surveys the different methods employed for this purpose. This review category and delineates several detections and counting estimation methods that have been applied for the examination of scenes from static and moving platforms.

Keywords: crowd; counting; holistic and local motion features; estimation; visual surveillance; moving platform; computer vision.

DOI: 10.1504/IJCVR.2019.099435

International Journal of Computational Vision and Robotics, 2019 Vol.9 No.3, pp.228 - 259

Received: 28 Oct 2017
Accepted: 27 Feb 2018
Published online: 02 May 2019 *

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