Surveillance of crowded places can benefit from improved techniques of anomaly detection
in crowd videos. Several existing methods have detected various types of crowd abnormal …

Automatic Anomaly detection in a crowd scene is very significant because of more
apprehension with people's safety in a public place. Because of usefulness and complexity …

Crowd anomaly detection is a key research area in vision-based surveillance. Most of the
crowd anomaly detection algorithms are either too slow, bulky, or power-hungry to be …

Recently, due to its widespread applications in public safety, anomaly detection in crowd
scenes has become a hot topic. Some deep-learning-based methods attain significant …

We propose an anomaly detection approach by learning a generative model using deep
neural network. A weighted convolutional autoencoder‐(AE‐) long short‐term memory …

Automated crowd anomaly detection and crowd scene analysis is a novel and emerging
field of computer science and engineering domain. The analysis of crowd behavior based …

With the increasing population, the probability of occurrence of different kinds of crowd
anomalies gets frequent. Blockage on roads, the lighting condition, and the uneven …

This study proposed an AlexNet-based crowd anomaly detection model in the video (image
frames). The proposed model was comprised of four convolution layers (CLs) and three …

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 …

In this work, we propose an unsupervised approach for crowd scene anomaly detection and
localization using a social network model. Using a window-based approach, a video scene …