An adaptive training-less system for anomaly detection in crowd scenes
A Sikdar, AS Chowdhury - arXiv preprint arXiv:1906.00705, 2019 - arxiv.org
Anomaly detection in crowd videos has become a popular area of research for the computer
vision community. Several existing methods generally perform a prior training about the …
vision community. Several existing methods generally perform a prior training about the …
An adaptive training-less framework for anomaly detection in crowd scenes
A Sikdar, AS Chowdhury - Neurocomputing, 2020 - Elsevier
Anomaly detection in crowd videos has become a popular area of research for the computer
vision community. Several existing methods have determined anomaly as a deviation from …
vision community. Several existing methods have determined anomaly as a deviation from …
[HTML][HTML] Crowd anomaly detection via spatial constraints and meaningful perturbation
J Feng, D Wang, L Zhang - ISPRS International Journal of Geo …, 2022 - mdpi.com
Crowd anomaly detection is a practical and challenging problem to computer vision and
VideoGIS due to abnormal events' rare and diverse nature. Consequently, traditional …
VideoGIS due to abnormal events' rare and diverse nature. Consequently, traditional …
Unsupervised fast anomaly detection in crowds
In this paper, we proposed a fast and robust unsupervised framework for anomaly detection
and localization in crowed scenes. Our method avoids modeling the normal state of the …
and localization in crowed scenes. Our method avoids modeling the normal state of the …
Robust anomaly detection via fusion of appearance and motion features
Anomaly detection in crowded scenes is an important issue in computer vision. In this paper,
we propose a novel framework which takes both appearance and motion characteristics into …
we propose a novel framework which takes both appearance and motion characteristics into …
Deep learning and one-class SVM based anomalous crowd detection
Anomalous event detection in videos is an important and challenging task. This paper
proposes a deep representation approach to the problem, which extracts and represents …
proposes a deep representation approach to the problem, which extracts and represents …
Deep Crowd Anomaly Detection: State-of-the-Art, Challenges, and Future Research Directions
MH Sharif, L Jiao, CW Omlin - arXiv preprint arXiv:2210.13927, 2022 - arxiv.org
Crowd anomaly detection is one of the most popular topics in computer vision in the context
of smart cities. A plethora of deep learning methods have been proposed that generally …
of smart cities. A plethora of deep learning methods have been proposed that generally …
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 …
[HTML][HTML] An efficient anomaly detection system for crowded scenes using variational autoencoders
M Xu, X Yu, D Chen, C Wu, Y Jiang - Applied Sciences, 2019 - mdpi.com
Anomaly detection in crowded scenes is an important and challenging part of the intelligent
video surveillance system. As the deep neural networks make success in feature …
video surveillance system. As the deep neural networks make success in feature …
Anomaly detection in moving crowds through spatiotemporal autoencoding and additional attention
B Yang, J Cao, R Ni, L Zou - Advances in Multimedia, 2018 - Wiley Online Library
We propose an anomaly detection approach by learning a generative model using deep
neural network. A weighted convolutional autoencoder‐(AE‐) long short‐term memory …
neural network. A weighted convolutional autoencoder‐(AE‐) long short‐term memory …