[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 …
Taxonomy of anomaly detection techniques in crowd scenes
A Aldayri, W Albattah - Sensors, 2022 - mdpi.com
With the widespread use of closed-circuit television (CCTV) surveillance systems in public
areas, crowd anomaly detection has become an increasingly critical aspect of the intelligent …
areas, crowd anomaly detection has become an increasingly critical aspect of the intelligent …
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 …
Plug-and-play cnn for crowd motion analysis: An application in abnormal event detection
Most of the crowd abnormal event detection methods rely on complex hand-crafted features
to represent the crowd motion and appearance. Convolutional Neural Networks (CNN) have …
to represent the crowd motion and appearance. Convolutional Neural Networks (CNN) have …
Resnetcrowd: A residual deep learning architecture for crowd counting, violent behaviour detection and crowd density level classification
In this paper we propose ResnetCrowd, a deep residual architecture for simultaneous crowd
counting, violent behaviour detection and crowd density level classification. To train and …
counting, violent behaviour detection and crowd density level classification. To train and …
Deep learning approaches for video-based anomalous activity detection
The pervasive use of cameras at indoor and outdoor premises on account of recording the
activities has resulted into deluge of long video data. Such surveillance videos are …
activities has resulted into deluge of long video data. Such surveillance videos are …
Detecting violent and abnormal crowd activity using temporal analysis of grey level co-occurrence matrix (GLCM)-based texture measures
The severity of sustained injury resulting from assault-related violence can be minimised by
reducing detection time. However, it has been shown that human operators perform poorly …
reducing detection time. However, it has been shown that human operators perform poorly …
Spatio-temporal fall event detection in complex scenes using attention guided LSTM
Fall events are one of the greatest risks for public safety, especially in some complex scenes
with large number of people. Nevertheless, there are few researches on fall detection in …
with large number of people. Nevertheless, there are few researches on fall detection in …
We have to talk about emotional AI and crime
L Podoletz - AI & SOCIETY, 2023 - Springer
Emotional AI is an emerging technology used to make probabilistic predictions about the
emotional states of people using data sources, such as facial (micro)-movements, body …
emotional states of people using data sources, such as facial (micro)-movements, body …
Anomalous entities detection and localization in pedestrian flows
We propose a novel Gaussian kernel based integration model (GKIM) for anomalous entities
detection and localization in pedestrian flows. The GKIM integrates spatio-temporal features …
detection and localization in pedestrian flows. The GKIM integrates spatio-temporal features …