Open AccessSocial Distancing Detection Using Open CV and Yolo Object Detector
Author(s) -
IshaniGarkoti Akanksha Shukla
Publication year - 2021
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst070121
Subject(s) - social distance , pandemic , distancing , internet privacy , covid-19 , computer security , social psychology , psychology , computer science , medicine , infectious disease (medical specialty) , disease , pathology
Lately, social distancing has become a trending term, more because of the COVID-19 pandemic that hasaffected the entire world causing more than 1 million deaths. The world we lived in a few months prior iscompletely different from what it is now.The lack of any antidotes and the absence of immunity, capable offighting off the virus has made humans more undefended. Hence, Social Distancing is the only best option forus to protect ourselves from diseases, not limited to COVID-19, that may be transmitted through humancontact. Social distancing is a technique that may be used to reduce the rate of new cases during a pandemicoutbreak. This publication is focusing on surveillance of public places and detecting whether the people aremaintaining social distancing or not. It explains the development of technology through the use of AI-basedprocedures to detect whether the social distancing norm is followed or not, in any public video stream.The software embedded can distinguish between a person maintaining social distance (marked green) and aperson who is not (marked red) and will also keep a count of incidents where social distancing was notfollowed.