Indoor and Outdoor Crowd Density Level Estimation with Video Analysis through Machine Learning Models
arxiv(2024)
摘要
Crowd density level estimation is an essential aspect of crowd safety since
it helps to identify areas of probable overcrowding and required conditions.
Nowadays, AI systems can help in various sectors. Here for safety purposes or
many for public service crowd detection, tracking or estimating crowd level is
essential. So we decided to build an AI project to fulfil the purpose. This
project can detect crowds from images, videos, or webcams. From these images,
videos, or webcams, this system can detect, track and identify humans. This
system also can estimate the crowd level. Though this project is simple, it is
very effective, user-friendly, and less costly. Also, we trained our system
with a dataset. So our system also can predict the crowd. Though the AI system
is not a hundred percent accurate, this project is more than 97 percent
accurate. We also represent the dataset in a graphical way.
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