Video surveillance systems are popular and used in public places such as market places,
shopping malls, hospitals, banks, streets, education institutions, city administrative offices …

Videos represent the primary source of information for surveillance applications. Video
material is often available in large quantities but in most cases it contains little or no …

Anomaly detection in surveillance videos is currently a challenge because of the diversity of
possible events. We propose a deep convolutional neural network (CNN) that addresses …

Rapid developments in urbanization and autonomous industrial environments have
augmented and expedited the need for intelligent real-time video surveillance. Recent …

The detection of abnormal behaviour in crowded scenes has to deal with many challenges.
This paper presents an efficient method for detection and localization of anomalies in …

Anomalous event detection is of utmost importance in intelligent video surveillance.
Currently, most approaches for the automatic analysis of complex video scenes typically rely …

We present a novel unsupervised deep learning framework for anomalous event detection
in complex video scenes. While most existing works merely use hand-crafted appearance …

This paper proposes a fast and reliable method for anomaly detection and localization in
video data showing crowded scenes. Time-efficient anomaly localization is an ongoing …

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 …

Computer vision has evolved in the last decade as a key technology for numerous
applications replacing human supervision. Timely detection of traffic violations and …