Video surveillance systems are popular and used in public places such as market places,
shopping malls, hospitals, banks, streets, education institutions, city administrative offices …

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 …

In the last decade, crowd counting and localization attract much attention of researchers due
to its wide-spread applications, including crowd monitoring, public safety, space design, etc …

Detecting coherent groups is fundamentally important for crowd behavior analysis. In the
past few decades, plenty of works have been conducted on this topic, but most of them have …

This paper proposes a fast and reliable method for anomaly detection and localization in
video data showing crowded scenes. Time-efficient anomaly localization is an ongoing …

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 …

Any intelligent traffic monitoring system must be able to detect anomalies such as traffic
accidents in real-time. In this paper, we propose a Decision-Tree enabled approach …

In this paper we introduce a novel method to detect and localize abnormal behaviors in
crowd videos using Social Force model. For this purpose, a grid of particles is placed over …

Vision-based human action and activity recognition has an increasing importance among
the computer vision community with applications to visual surveillance, video retrieval and …

Crowded scene understanding is a fundamental problem in computer vision. In this study,
we develop a multi-task deep model to jointly learn and combine appearance and motion …