Texture classification-based feature processing for violence-based anomaly detection in crowded environments

AA Mohamed, F Alqahtani, A Shalaby… - Image and vision …, 2022 - Elsevier
Anomaly detection from video surveillance inputs helps to improve security in crowded
places and outdoors. The captured image is analyzed to identify human faces, objects, and …

Anomaly detection based on a 3d convolutional neural network combining convolutional block attention module using merged frames

IC Hwang, HS Kang - Sensors, 2023 - mdpi.com
With the recent rise in violent crime, the real-time situation analysis capabilities of the
prevalent closed-circuit television have been employed for the deterrence and resolution of …

Analysis of anomaly detection in surveillance video: recent trends and future vision

R Raja, PC Sharma, MR Mahmood… - Multimedia Tools and …, 2023 - Springer
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 …

[PDF][PDF] Bayesian Feed Forward Neural Network-Based Efficient Anomaly Detection from Surveillance Videos.

M Murugesan, S Thilagamani - Intelligent Automation & Soft …, 2022 - cdn.techscience.cn
Automatic anomaly activity detection is difficult in video surveillance applications due to
variations in size, type, shape, and objects' location. The traditional anomaly detection and …

[PDF][PDF] Detecting anomalies in security cameras with 3DCNN and ConvLSTM

EA Mahareek, EK El-Sayed, NM El-Desouky… - 2023 - academia.edu
This paper presents a new method for anomaly detection in surveillance videos using deep
learning. The proposed method is based on a deep network trained to identify objects and …

Temporal features-based anomaly detection from surveillance videos using deep learning techniques

P Mangai, MK Geetha… - … Conference on Artificial …, 2022 - ieeexplore.ieee.org
Automatic video surveillance is an active research area in recent times to enhance security
features. Based on the crowd behavior, the normal and abnormal scenarios can be detected …

[HTML][HTML] Human abnormal behavior detection using CNNs in crowded and uncrowded surveillance–A survey

P Kuppusamy, VC Bharathi - Measurement: Sensors, 2022 - Elsevier
The demand for surveillance networks is increasing universally on account of decreasing
the faith in people. This leads to monitor the people during working, roaming, traveling, and …

RETRACTED ARTICLE: A kernel support vector machine based anomaly detection using spatio-temporal motion pattern models in extremely crowded scenes

NK Priyadharsini, D Chitra - Journal of Ambient Intelligence and …, 2021 - Springer
Millions of security cameras were placed in public spaces, generating large quantities of
video data. There is a need to develop smart techniques to identify and classify objects …

An investigation of videos for abnormal behavior detection

A Patwal, M Diwakar, V Tripathi, P Singh - Procedia Computer Science, 2023 - Elsevier
The identification of abnormal behavior has several applications. There are several ways,
ranging from classical to deep learning based. It may be used to monitor campuses, banks …

Deep learning-based anomaly detection in video surveillance: A survey

HT Duong, VT Le, VT Hoang - Sensors, 2023 - mdpi.com
Anomaly detection in video surveillance is a highly developed subject that is attracting
increased attention from the research community. There is great demand for intelligent …