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

Surveillance of crowded places can benefit from improved techniques of anomaly detection
in crowd videos. Several existing methods have detected various types of crowd abnormal …

Abnormal crowd behavior detection is an important research issue in computer vision. The
traditional methods first extract the local spatio-temporal cuboid from video. Then the cuboid …

With the rapidly increasing demands from surveillance and security industries, crowd
behaviour analysis has become one of the hotly pursued video event detection frontiers …

Abnormal event detection in video surveillance is extremely important, especially for
crowded scenes. In recent years, many algorithms have been proposed based on hand …

Video Surveillance (VS) systems are popular. For enhancing the safety of public lives as
well as assets, it is utilized in public places like marketplaces, hospitals, streets, education …

In today's scenario, there are frequent events (viz. political rallies, live concerts, strikes,
sports meet) occur in which many people gather to participate in the event. In crowded areas …

Aiming at the high complexity of existing crowd abnormal detection models, the inability of
traditional CNN to extract time-related features, and the lack of training samples, an …

Anomaly detection in crowded scenes plays a crucial role in automatic video surveillance to
avert any casualty in the areas witnessing the high amount of footfalls. The key challenge for …

In this paper, we present a hybrid deep network based approach for crowd anomaly
detection in videos. For improved performance, the proposed approach exploits deep and …