Scopus; WoS

A Real-time Crowd Density Level Detection System

Năm XB 2023 Tạp chí / Hội thảo Advances in Information and Communication Technology DOI / Link https://doi.org/10.1007/978-3-031-49529-8_12 ↗

Tác giả

Tóm tắt

Crowd density level evaluates the number of people gathering in a particular area or scene, typically based on videos generated from real-time closed-circuit television (CCTV) cameras. The goal of estimating the levels of a crowd is to provide accurate and reliable information about the crowd size and density, which can be helpful in various situations. Furthermore, detecting and analyzing crowds in real-time is a crucial task for many applications such as monitoring large crowds in public areas, detecting any suspicious activities or potential threats; managing crowds in public places to prevent overcrowding and ensure the safety of individuals; monitoring the flow of people in an event to optimize the use of security officers and facilities. In this paper, we present a deep learning-based architecture and system for detecting levels of crowd density from CCTV cameras. In particular, the system can automatically generate alert information when identifying high-density camera areas, enabling security staff to take corrective measures to manage the crowd and prevent overcrowding before it happens. The proposed system provides a reliable approach for real-time crowd detection, which can be integrated into existing surveillance systems.

Tài liệu tham khảo

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