This paper is published in Volume-7, Issue-3, 2021
Area
Computer Engineering
Author
Vishal Singh, Keyur Madane, Himanshu Sugandhi, Ankit Joshi, B. S. Satpute
Org/Univ
Dr. D. Y. Patil Institute of Technology, Pune, Maharashtra, India
Pub. Date
14 June, 2021
Paper ID
V7I3-1859
Publisher
Keywords
CNN, Spatio-Temporal Autoencoder

Citationsacebook

IEEE
Vishal Singh, Keyur Madane, Himanshu Sugandhi, Ankit Joshi, B. S. Satpute. Video anomaly detection, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Vishal Singh, Keyur Madane, Himanshu Sugandhi, Ankit Joshi, B. S. Satpute (2021). Video anomaly detection. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.

MLA
Vishal Singh, Keyur Madane, Himanshu Sugandhi, Ankit Joshi, B. S. Satpute. "Video anomaly detection." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.

Abstract

Security is always a main concern in every domain, due to a rise in crime rate in crowded events or suspicious lonely areas. Abnormal detection and monitoring have major applications of computer vision to tackle various problems. Due to the growing demand in the protection of safety, security, and personal properties, the needs and deployment of video surveillance systems can catch all the anomaly and anomalies play important role in surveillance detection. Anomaly detection is used to identify the odd pattern or abnormal behaviors in the surrounding. Surveillance videos are able to capture and store a variety of anomalies in the surrounding. People detection and tracking are of important research fields that have gained a lot of attention in the last few years. Most of the time, the timely and accurate detection of video anomalies is the main objective of security applications. The video anomalies such as anomalous activities and anomalous entities are defined as abnormal or irregular events that are different from normal events happening every day. In this paper, we present how surveillance videos are used to detect anomalies.