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 …

As the monitor probes are used more and more widely these days, the task of detecting
abnormal behaviors in surveillance videos has gained widespread attention. The …

This paper describes a method for learning anomaly behavior in the video by finding an
attention region from spatiotemporal information, in contrast to the full-frame learning. In our …

Traditional video surveillance systems detect abnormal events via human involvement,
which is exhausting and erroneous, while computer vision-based automated anomaly …

In the present technological world, surveillance cameras generate an immense amount of
video data from various sources, making its scrutiny tough for computer vision specialists. It …

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 …

Anomalous activity recognition deals with identifying the patterns and events that vary from
the normal stream. In a surveillance paradigm, these events range from abuse to fighting …

The recognition of abnormal behavior in surveillance video is the focus of current research,
which has high research value and broad application possibilities. Its main applications are …

Anomalous event detection in any surveillance system has become an important area of
research to make the surveillance effective and real time. In recent years, deep learning …

Surveillance systems regularly create massive video data in the modern technological era,
making their analysis challenging for security specialists. Finding anomalous activities …