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

Suspicious human activity recognition from surveillance video is an active research area of
image processing and computer vision. Through the visual surveillance, human activities …

Sparse coding-based anomaly detection has shown promising performance, of which the
keys are feature learning, sparse representation, and dictionary learning. In this paper, we …

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 …

The detection of anomalous behaviors in automated video surveillance is a recurrent topic in
recent computer vision research. Depending on the application field, anomalies can present …

Speedy abnormal event detection meets the growing demand to process an enormous
number of surveillance videos. Based on inherent redundancy of video structures, we …

Anomalies are rare and anomaly detection is often therefore framed as One-Class
Classification (OCC), ie trained solely on normalcy. Leading OCC techniques constrain the …

The detection and localization of anomalous behaviors in crowded scenes is considered,
and a joint detector of temporal and spatial anomalies is proposed. The proposed detector is …

This paper addresses the problem of joint detection and recounting of abnormal events in
videos. Recounting of abnormal events, ie, explaining why they are judged to be abnormal …

We present a novel end-to-end partially supervised deep learning approach for video
anomaly detection and localization using only normal samples. The insight that motivates …