Crowd management and monitoring is crucial for maintaining public safety and is an
important research topic. Developing a robust crowd monitoring system (CMS) is a …

Crowd tracking and analysis of crowd behavior is a challenging research area in computer
vision. In today's crowded environment manual surveillance systems are inefficient, labor …

Crowd counting in high density crowds has significant importance in crowd safety and crowd
management. Existing state-of-the-art methods employ regression models to count the …

Counting and localization of people in videos consisting of low density to high density
crowds encounter many key challenges including complex backgrounds, scale variations …

The constantly developing urbanization and the emergence of smart cities require better
security surveillance and crowd monitoring systems. The growing availability of the Internet …

Object detection using deep learning has attracted considerable interest from researchers
because of its competency in performing state-of-the-art tasks, including detection …

Introduction Hand gestures are an effective communication tool that may convey a wealth of
information in a variety of sectors, including medical and education. E-learning has grown …

Anomaly detection and behavioral recognition are key research areas widely used to
improve human safety. However, in recent times, with the extensive use of surveillance …

In the past ten years, crowd detection and counting have been applied in many fields such
as station crowd statistics, urban safety prevention, and people flow statistics. However …

Crowd density estimation is an important topic in computer vision due to its widespread
applications in surveillance, urban planning, and intelligence gathering. Resulting from …