Crowd Monitoring System Using Facial Recognition

Title

Crowd Monitoring System Using Facial Recognition

Creator

Das S.; Chinnaiyan R.; Sabarmathi G.; Maskey A.; Swarnamugi M.; Balachandar S.; Divya R.

Description

The World Health Organization (WHO) suggests social isolation as a remedy to lessen the transmission of COVID-19 in public areas. Most countries and national health authorities have established the 2-m 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 manymore. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Smart Innovation, Systems and Technologies, Vol-371, pp. 567-577.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Crowd Monitoring and Analysis; Face landmark estimation; Histogram of Gradient (HOG); K-Nearest Neighbor (KNN); Support Vector Machine (SVM)

Coverage

Das S., Department of CSE-Cyber Security, JAIN (Deemed-to-be-University), Bengaluru, India; Chinnaiyan R., Department of CSE, Alliance College of Engineering and Design, Alliance University, Bengaluru, India; Sabarmathi G., School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Maskey A., Department of CSE-Cyber Security, JAIN (Deemed-to-be-University), Bengaluru, India; Swarnamugi M., Department of CS, Jyoti Nivas College, Bengaluru, India; Balachandar S., VTU-RC, MCA, CMR Insitute of Technology, Bengaluru, India; Divya R., VTU-RC, MCA, CMR Insitute of Technology, Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 21903018; ISBN: 978-981996705-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-99-6706-3_50

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178634981&doi=10.1007%2f978-981-99-6706-3_50&partnerID=40&md5=5ec379f6ec52617ce6ca5d24f3901721