Intelligent video surveillance: a review through deep learning techniques for crowd analysis

G Sreenu, S Durai - Journal of Big Data, 2019 - Springer
Big data applications are consuming most of the space in industry and research area.
Among the widespread examples of big data, the role of video streams from CCTV cameras …

Human activity recognition: Review, taxonomy and open challenges

MH Arshad, M Bilal, A Gani - Sensors, 2022 - mdpi.com
Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains,
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …

Vision-based human activity recognition: a survey

DR Beddiar, B Nini, M Sabokrou, A Hadid - Multimedia Tools and …, 2020 - Springer
Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …

A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance

K Rezaee, SM Rezakhani, MR Khosravi… - Personal and Ubiquitous …, 2024 - Springer
Fast and automated recognizing of abnormal behaviors in crowded scenes is significantly
effective in increasing public security. The traditional procedure of recognizing abnormalities …

[HTML][HTML] A roadmap for the future of crowd safety research and practice: Introducing the Swiss Cheese Model of Crowd Safety and the imperative of a Vision Zero …

M Haghani, M Coughlan, B Crabb, A Dierickx… - Safety science, 2023 - Elsevier
Crowds can be subject to intrinsic and extrinsic sources of risk, and previous records have
shown that, in the absence of adequate safety measures, these sources of risk can …

Mapping the knowledge domain of soft computing applications for emergency evacuation studies: A scientometric analysis and critical review

B Liang, CN van der Wal, K Xie, Y Chen, FMT Brazier… - Safety science, 2023 - Elsevier
Emergency evacuation is viewed as a common strategy adopted during the disaster
preparedness stage of evacuation to ensure the safety of potentially affected populations. In …

Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects

FL Sánchez, I Hupont, S Tabik, F Herrera - Information Fusion, 2020 - Elsevier
Crowd behaviour analysis is an emerging research area. Due to its novelty, a proper
taxonomy to organise its different sub-tasks is still missing. This paper proposes a taxonomic …

A review of deep learning techniques for crowd behavior analysis

B Tyagi, S Nigam, R Singh - Archives of Computational Methods in …, 2022 - Springer
In today's scenario, there are frequent events (viz. political rallies, live concerts, strikes,
sports meet) occur in which many people gather to participate in the event. In crowded areas …

Learning Models in Crowd Analysis: A Review

S Goel, D Koundal, R Nijhawan - Archives of Computational Methods in …, 2024 - Springer
Crowd detection and counting are important tasks in several applications of crowd analysis
including traffic management, public safety and event planning. Automatic crowd counting …

Event detection in surveillance videos: a review

A Karbalaie, F Abtahi, M Sjöström - Multimedia tools and applications, 2022 - Springer
Since 2008, a variety of systems have been designed to detect events in security cameras.
There are also more than a hundred journal articles and conference papers published in this …