Crowd Monitoring System Using Facial Recognition

Abstract

The World Health Organization (WHO) suggests social isolation as a remedy to lessen the transmission of COVID19 in public areas. Most countries and national health authorities have established the 2m physical distance as a required safety measure in shopping malls, schools, and other covered locations. In this study, we use standard CCTV security cameras to create an automated system for people detecting crowds in indoor and outdoor settings. Popular computer vision algorithms and the CNN model are implemented to build up the system and a comparative study is performed with algorithms like Support Vector Machine and KNN algorithm. The created model is a general and precise people tracking and identifying the solution that may be used in a wide range of other study areas where the focus is on person detection, including autonomous cars, anomaly detection, crowd analysis, and many more. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.