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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …