Pernechele, C.C.PernecheleGrandis, N.N.GrandisBondanza, I.I.BondanzaCapucci, AACapucciLessio, L.L.LessioPaoletti, L.L.PaolettiSparc, S.S.SparcTomasin, M.M.TomasinYusupova, R.R.Yusupova2023-07-122023-07-1220220037-8720http://hdl.handle.net/20.500.12386/34273We are grateful to INAF and MUR for support this job by means of dedicated covid-contrast funds.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.STAMPAenArticlehttps://memsait.oa-roma.inaf.it/wp-content/uploads/2022/10/2022MmSAI..1...91P.pdfhttps://memsait.oa-roma.inaf.it/index.php/2022/07/25/vol-93-1/FIS/07 - FISICA APPLICATA (A BENI CULTURALI, AMBIENTALI, BIOLOGIA E MEDICINA)