Work

Detection of Crowd concentrations with YOLO V3

Year: 2023

Type: article

Abstract: Crowd detection using street cameras has attracted a lot of research in recent years. In this paper, we propose a simple, fast, and effective method using YOLOv3 model for crowd detection. Using image frames extracted from surveillance video, pedestrian objects are detected, counted and a warning signal is sent out when a crowd occurs. The obtained results on test data extracted from 2 data sets STCrowd, SmartCity, and our self-collected dataset confirm the feasibility of the proposed method.

Source: CTU Journal of Innovation and Sustainable Development

DOI: 10.22144/ctujoisd.2023.035

Authors: Ba Duy Nguyen, Thanh Nhan Dinh, Thanh Bach Nguyen, Quoc Dinh Truong

Institutions: Trường Đại học Kỹ thuật - Công nghệ Cần Thơ, Can Tho University

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: diamond

OpenAlex ID: W4388024104

FWCI:

Cites: 8

Cited by:

Related to: 10