Comprehensive survey on video anomaly detection using deep learning techniques Online publication date: Thu, 04-Jul-2024
by Sreedevi R. Krishnan; P. Amudha; S. Sivakumari
International Journal of Computational Vision and Robotics (IJCVR), Vol. 14, No. 4, 2024
Abstract: The rapid increase in violence and crime leads to the use of video surveillance systems. Handling such huge videos and classifying them as abnormal or not are tedious. Therefore, an automatic anomaly detection method is vital for the real-time detection of anomalous events. Advancements in machine intelligence lead to an automatic anomaly detection system for the timely identification of anomalous events and reducing the after-effects. Recent research uses deep learning techniques for faster and automatic detection of abnormal events from an enormous volume of surveillance videos. Reviewing the video anomaly detection system is very relevant and helps to promote future research in this area. The paper performs a comprehensive study of several video anomaly detection methods using deep learning techniques to detect and predict anomalous events. The paper also surveys various methods used for women's safety. Various methodologies, datasets, and evaluation metrics for detecting video anomalies and comparisons are included.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Vision and Robotics (IJCVR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook