A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Automated scene analysis has been a topic of great interest in computer vision and
cognitive science. Recently, with the growth of crowd phenomena in the real world, crowded …

Abnormal behavior detection in crowd scenes is continuously a challenge in the field of
computer vision. For tackling this problem, this paper starts from a novel structure modeling …

We introduce a novel method for abnormal crowd event detection in surveillance videos.
Particularly, our work focuses on panic and escape behavior detection that may appear …

Aim: Current crime behavior observation has the problem of not being real time, thus
criminal behavior cannot be promptly controlled. To improve the control of criminal behavior …

We propose a novel Gaussian kernel based integration model (GKIM) for anomalous entities
detection and localization in pedestrian flows. The GKIM integrates spatio-temporal features …

Visual recognition of crowd dynamics has had a huge impact on several applications
including surveillance, situation awareness, homeland security and intelligent environments …

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 …

The crowd stampede and terrorist attacks in public areas have now become more serious
and dangerous threats due to the rapid increase in the population and scale of cities …

Crime generates significant losses, both human and economic. Every year, billions of dollars
are lost due to attacks, crimes, and scams. Surveillance video camera networks generate …