Detection-based methods have been viewed unfavorably in crowd analysis due to their poor
performance in dense crowds. However, we argue that the potential of these methods has …

In recent years, anomaly events detection in crowd scenes attracts many researchers'
attentions, because of its importance to public safety. Existing methods usually exploit visual …

Population growth has made the probability of incidents at large-scale crowd events higher
than ever. In the past decades, automated crowd scene analysis done by computer vision …

Violence is a critical social problem and demands to evaluate through computer vision
approaches. At present, the incidences of violent actions get grown in the community …

We propose an anomaly detection approach by learning a generative model of moving
pedestrians to guarantee public safety. To resolve the existing challenges of anomaly …

Crowd anomaly detection has been a research hotspot in the field of video surveillance in
recent years. In most existing methods, the accuracy of anomaly detection dominantly relies …

In this digital era, the complexity-efficient anomaly concentration becomes a major concern
for the surveillance systems. This paper addresses the issue with an efficient and rapid …

The detection of crowd density levels and anomalies is a hot topic in video surveillance.
Especially in human-centric action and activity-based movements. In some respects, the …

This paper presents a novel method for global anomaly detection in crowded scenes. The
optical flow of frames is used to extract the foreground of areas with people motions in the …

Security surveillance is critical to social harmony and people's peaceful life. It has a great
impact on strengthening social stability and life safeguarding. Detecting anomaly timely …