This chapter presents a review and systematic comparison of the state of the art on crowd
video analysis. The rationale of our review is justified by a recent increase in intelligent …

Video anomaly detection plays a critical role for intelligent video surveillance. We present an
abnormal video event detection system that considers both spatial and temporal contexts. To …

People naturally escape from a place when unexpected events happen. Based on this
observation, efficient detection of crowd escape behavior in surveillance videos is a …

This paper addresses the problem of detecting and localizing abnormal activities in crowded
scenes. A spatiotemporal Laplacian eigenmap method is proposed to extract different crowd …

Analyzing crowd events in a video is key to understanding the behavioral characteristics of
people (humans). Detecting crowd events in videos is challenging because of articulated …

In this paper, we propose a novel algorithm based on the acceleration feature to detect
anomalous crowd behaviors in video surveillance systems. Different from the previous work …

In this paper, we propose a novel framework for anomalous crowd behavior detection and
localization by introducing divergent centers in intelligent video surveillance systems. In this …

Video processing algorithms are widely used in applications related to computer vision such
as motion tracking, human behavior understanding, event detection and localization …

Analysis of crowd behaviour in public places is an indispensable tool for video surveillance.
Automated detection of anomalous crowd behaviour is a critical problem with the increase in …

In this paper, we propose a novel algorithm by jointly modeling motion and context
information targeting at detecting abnormal events in crowded scenes. In our algorithm …