When overpopulated cities face frequent crowded events like strikes, demonstrations,
parades or other sorts of people gatherings, they are confronted to multiple security issues …

Surveillance videos are able to capture a variety of realistic anomalies. In this paper, we
propose to learn anomalies by exploiting both normal and anomalous videos. To avoid …

This article aims to summarize and describe research on the topic of automatic group
emotion recognition. In recent years, the topic of emotion analysis of groups or crowds has …

Estimating crowd count in densely crowded scenes is an extremely challenging task due to
non-uniform scale variations. In this paper, we propose a novel end-to-end cascaded …

In this paper we address the abnormality detection problem in crowded scenes. We propose
to use Generative Adversarial Nets (GANs), which are trained using normal frames and …

In current technological era, surveillance systems generate an enormous volume of video
data on a daily basis, making its analysis a difficult task for computer vision experts …

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 …

Motivated by our observation that motion information is the key to good anomaly detection
performance in video, we propose a temporal augmented network to learn a motion-aware …

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

Abnormal crowd behaviour detection attracts a large interest due to its importance in video
surveillance scenarios. However, the ambiguity and the lack of sufficient abnormal ground …