Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …

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

In this paper, we focus mainly on designing a Multi-Target Object Tracking algorithm that
would produce high-quality trajectories while maintaining low computational costs. Using …

Building upon state-of-the-art algorithms for pedestrian detection and multi-object tracking,
and inspired by sociological models of human collective behavior, we automatically detect …

Over the years, object tracking and detection has emerged as one of the most important
aspects of UAV applications such as surveillance, reconnaissance, etc. In our paper, we …

On July 24, 2010, 21 people died and more than 500 were injured in a stampede at the
Loveparade, a music festival, in Duisburg, Germany. Although this tragic incident is but one …

Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases
such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles …

In this work, we propose an unsupervised approach for crowd scene anomaly detection and
localization using a social network model. Using a window-based approach, a video scene …

Anomaly detection is still a challenging task for video surveillance due to complex
environments and unpredictable human behaviors. Most existing approaches train offline …

This paper presents a solution for Track 1 of the AI City Challenge 2023, which involves
Multi-Camera People Tracking in indoor scenarios. The proposed framework comprises four …