Fast and automated recognizing of abnormal behaviors in crowded scenes is significantly
effective in increasing public security. The traditional procedure of recognizing abnormalities …

Abnormal crowd behavior detection has recently attracted increasing attention due to its
wide applications in computer vision research areas. However, it is still an extremely …

Detecting abnormal crowd motion emerging from complex interactions of individuals is
paramount to ensure the safety of crowds. Crowd-level abnormal behaviors (CABs), eg …

Crowd flow anomaly detection (CFAD) plays a vital role in ensuring public safety due to its
capability to distinguish abnormal crowd movement behaviors from the norm. However, the …

Detecting anomalous crowd behavioral patterns from videos is an important task in video
surveillance and maintaining public safety. In this work, we propose a novel architecture to …

Anomaly detection in crowd scene has attracted an increasing attention in video
surveillance, but a precise detection still remains a challenge. This paper presents a novel …

In this study, we propose a neural network to solve crowd counting, localization and
abnormal event detection problems together. Our proposed model combines P2P-Net with a …

In recent years, malignant crowd incidents that endanger public safety occur frequently,
which alarms humans of the security in public areas. Focus on the detection of abnormal …

Abnormal behavior detection in crowded scenes is extremely challenging in the field of
computer vision due to severe inter-object occlusions, varying crowd densities and the …

In this paper we propose a novel approach to detect anomalies in crowded scenes. This is
achieved by analyzing the crowd behavior by extracting the corner features. For each corner …