Published Paper Details:

The report presents a strategy for social distancing detection, the unprecedented outbreak of the 2019 novel coronavirus, termed as COVID-19 by the globe Health Organization (WHO), has placed numerous governments round the world in an exceedingly precarious position. The effect of the COVID-19 outbreaks, in advance witnessed through the residents of China alone, has now become a matter of grave concern for virtually every country within the world. The shortage of assets to undergo the COVID-19 outbreak mixed with the worry of overburdened healthcare systems has forced a majority of those countries into a state of partial or complete lockdown. The number of laboratories confirmed coronavirus cases has been increasing at an alarming rate throughout the planet, with reportedly quite 2.2 million confirmed cases as on 20 April 2020. So, maintaining social distancing is incredibly important. to gauge the space between people to mitigate the impact of this coronavirus pandemic. The detection tool was developed to alert people to take care of a secure distance with one another by evaluating a video feed. The video frame from the camera was used as input, and therefore the open-source object detection pre- trained model supported the YOLOv3 algorithm was employed for pedestrian detection. Later, the video frame was transformed into top-down view for distance measurement from the 2D plane. the gap between people is often estimated and any noncompliant pair of individuals within the display are going to be indicated with a red frame and line. The proposed method was validated on a pre-recorded video of pedestrians walking on the road. The result shows that the proposed method is ready to work out the social distancing measures between multiple people within the video. The developed technique will be further developed as a detection tool in real-time application.