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During the COVID-19 pandemic it is necessary, to prevent contagion, to keep a safe distance from other individuals, in particular in public places. This project was created to provide a tool that, through Neural Networks and Artificial Vision, exploits images collected by surveillance video systems, producing useful information for respecting in…
The goal of this project is to implement a committee-based tracking ensemble model for human detection and tracking. This repository contains ML models and FairMOT implementation.
The YOLOv8-SORT-Human-Tracking repository demonstrates human tracking using YOLOv8 and the SORT algorithm, showcasing results of using YOLOv8 alone versus the combined method.
System integrated with YOLOv4 and Deep SORT for real-time crowd monitoring, then perform crowd analysis. The system is able to monitor for abnormal crowd activity, social distance violation and restricted entry. The other part of the system can then process crowd movement data into optical flow, heatmap and energy graph.