Citation

Fiandeiro M, Nguyen TT, Wong H, Hsu EB. Journal of Acute Medicine 2023; 13(1): 4-11.

Copyright

(Copyright © 2023, Taiwan Society of Emergency Medicine, Publisher iPress)

DOI

10.6705/j.jacme.202303_13(1).0002

PMID

37089669

PMCID

PMC10116033

Abstract

Estimation of crowd size for large gatherings is an indispensable metric for event planners, local authorities, and emergency management. Currently, most crowd counting relies on dated methods such as people counters, entrance sensors, and ticket sales. Over the past decade, there has been rapid development in crowd counting techniques and related technology. Despite progress, theoretical advances in crowd counting technology have outpaced practical applications. The emergence of the vast array of crowd counting techniques has added to the challenge of determining those advances that can be most readily implemented. This article aims to provide an overview of promising crowd counting strategies and recent developments applied within the disaster medicine context along with the best use cases and limitations.

Language: en

Keywords

review; convolutional neural network (CNN); crowd counting; drones