Dependable utilization of computer vision applications, such as smart surveillance, requires
training deep learning networks on datasets that sufficiently represent the classes of interest …

Dependable utilization of computer vision applications, such as smart surveillance, requires
training deep learning networks on datasets that sufficiently represent the classes of interest …

Terror attacks are often targeted towards the civilians gathered in one location (eg, Boston
Marathon bombing). Distinguishing such'malicious' scenes from the'normal'ones, which are …

Crowd behavior recognition plays a critical role in various domains, including public safety,
event management, and urban planning. Understanding crowd dynamics and detecting …

The detection of crowd behavior is critical for public safety and overall monitoring. A smart AI-
based surveillance system is therefore necessary to monitor and detect crowd behavior …

Approaches inspired by Newtonian mechanics have been successfully applied for detecting
abnormal behaviors in crowd scenarios, being the most notable example the Social Force …

In this work, we extract rich representations of crowd behavior from video using a fine-tuned
deep convolutional neural residual network. Using spatial partitioning trees we create …

Automatic video surveillance in public crowded places has been an active research area for
security purposes. Traditional approaches try to solve the crowd behavior recognition task …

Crowd behaviour analysis forms a central basis for having peaceful event organization, with
a minimum calamitous situation in the place of public congregation. Conventionally, the …

Surveillance systems currently deploy a variety of devices that can capture visual content
(such as CCTV, body-worn cameras, and smartphone cameras), thus rendering the …