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

Anomalous event detection is of utmost importance in intelligent video surveillance.
Currently, most approaches for the automatic analysis of complex video scenes typically rely …

In emergency situations, actions that save lives and limit the impact of hazards are crucial. In
order to act, situational awareness is needed to decide what to do. Geolocalized photos and …

Abnormal event detection is an important task in video surveillance systems. In this paper,
we propose novel bidirectional multi-scale aggregation networks (BMAN) for abnormal …

Learning-based video compression has achieved substantial progress during recent years.
The most influential approaches adopt deep neural networks (DNNs) to remove spatial and …

The emerging information revolution makes it necessary to manage vast amounts of
unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors …

The aim of this paper is to detect abnormal events in video streams, a challenging but
important subject in video surveillance. We propose a novel algorithm to address this …

This paper presents a novel video descriptor, referred to as Histogram of Oriented Track lets,
for recognizing abnormal situation in crowded scenes. Unlike standard approaches that use …

Crowd behavior analysis has recently emerged as an increasingly important and dedicated
problem for crowd monitoring and management in the visual surveillance community. In …

Featured Application The proposed methodology is an image processing application for
monitoring and recognizing human behaviors and has been evaluated over well-known …