Omnidirectional people's gathering monitoring by using deep learning algorithms
Date Issued
2022
Author(s)
•
Grandis, N.
•
Bondanza, I.
•
Capucci, A
•
•
•
Sparc, S.
•
Tomasin, M.
•
Yusupova, R.
Description
We are grateful to INAF and MUR for support this job by means of dedicated covid-contrast funds.
Abstract
It has long been recognized as gathering of people is one of the major risk factor
in spreading of viral epidemics. Social distancing is then one of the most simple and powerful
system to mitigate the spread of infections.We explore here the possibility of monitoring
public people’s gathering by using a novel bifocal omnidirectional lens designed by INAF
jointly with deep learning-based algorithms. The paper briefly describe how the lens works,
the applied deep learning algorithms and the preliminary results of the trials.
Volume
93
Start page
91
Issn Identifier
0037-8720
Rights
open.access
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