Abstract

This paper presents a methodology for detecting social distance using deep learning and computer vision between people to control the spread of covid-19. This application is developed to give alerts to people for maintaining social distance in crowded places. By using pre-recorded video as input and the open-source object detection pretrained model using the YOLOv3 algorithm We can tell if people are following social distancing or not and based on that we are creating red or green bounding boxes over it. It is also working on web cameras, CCTV, etc, and can detect people in real-time. This may help authorities to redesign the layout of public places or to take precautionary actions to mitigate high-risk zones.it can be used in other fields also like autonomous vehicles, human action recognition, crowd analysis.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.