Intelligent video surveillance: a review through deep learning techniques for crowd analysis
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 …
Among the widespread examples of big data, the role of video streams from CCTV cameras …
Analysis of anomaly detection in surveillance video: recent trends and future vision
Video Surveillance (VS) systems are popular. For enhancing the safety of public lives as
well as assets, it is utilized in public places like marketplaces, hospitals, streets, education …
well as assets, it is utilized in public places like marketplaces, hospitals, streets, education …
Advances and trends in real time visual crowd analysis
Real time crowd analysis represents an active area of research within the computer vision
community in general and scene analysis in particular. Over the last 10 years, various …
community in general and scene analysis in particular. Over the last 10 years, various …
Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects
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 …
taxonomy to organise its different sub-tasks is still missing. This paper proposes a taxonomic …
Convolutional neural networks for crowd behaviour analysis: a survey
Interest in automatic crowd behaviour analysis has grown considerably in the last few years.
Crowd behaviour analysis has become an integral part all over the world for ensuring …
Crowd behaviour analysis has become an integral part all over the world for ensuring …
Learning deep event models for crowd anomaly detection
Y Feng, Y Yuan, X Lu - Neurocomputing, 2017 - Elsevier
Abnormal event detection in video surveillance is extremely important, especially for
crowded scenes. In recent years, many algorithms have been proposed based on hand …
crowded scenes. In recent years, many algorithms have been proposed based on hand …
Slime Mold optimization with hybrid deep learning enabled crowd-counting approach in video surveillance
Z Xu, DK Jain, P Shamsolmoali, A Goli… - Neural Computing and …, 2024 - Springer
Crowd counting (CC) and density estimation are crucial for ensuring public safety and
security in surveillance videos with large audiences. As computer vision-based scene …
security in surveillance videos with large audiences. As computer vision-based scene …
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 …
effective in increasing public security. The traditional procedure of recognizing abnormalities …
[HTML][HTML] Recent trends in crowd analysis: A review
When overpopulated cities face frequent crowded events like strikes, demonstrations,
parades or other sorts of people gatherings, they are confronted to multiple security issues …
parades or other sorts of people gatherings, they are confronted to multiple security issues …
Crowd analysis using computer vision techniques
This article presents a survey on crowd analysis using computer vision techniques, covering
different aspects such as people tracking, crowd density estimation, event detection …
different aspects such as people tracking, crowd density estimation, event detection …