Crowd Density Estimation in Public Areas using Yolo

TITLE	Crowd Density Estimation in Public Areas using Yolo
ABSTRACT	The estimation of the density of the crowd is a critical task to guarantee public safety, the efficient management of the crowd and the prevention of disasters in highly populated areas. The classic techniques tend to combat issues of occlusion, fluctuating light and evolving motion of the mob. In this work, we propose the use of its sole framework for detection (YOLO) to estimate the density of the crowd in real time. The rapid and precise human detection capacity of Yolo allows the identification and effective counting of individuals in different crowd scenarios. The detected people are analyzed additionally to determine density levels, which can be classified as low, medium or high. As evidenced by experimental assessment conducted in reference data sets, Yolo is flexible in handling high crowd density and sustaining high real-time detection and performance accuracy.
AUTHOR	Raghunandan N V, Santhosh S G
PUBLICATION DATE	2025-09-03 18:59:21
VOLUME	13
ISSUE	3
DOI	DOI: 10.15662/IJMSERH.2025.1303068
PDF	pdf/2025/7/68_Crowd Density Estimation in Public Areas using Yolo.pdf
KEYWORDS

Article