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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: August 2022

Volume 7 | Issue 8

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Paper Title: Social Distancing Detection using Deep Learning Model
Authors Name: Mrs.D.Mohanapriya , A.Kiruthika , A.Megavardhini , K.Nandhini , P.Devayani
Unique Id: IJSDR2104069
Published In: Volume 6 Issue 4, April-2021
Abstract: Social distancing is possibly the only way to contain the spread of COVID-19. Recently, AI teams are created Social Distancing Tools using the concepts of Computer Vision. This project is inspired by their work. This project proposes a methodology to detect social distance using deep learning for the evaluation of distance between people to mitigate the impact of this corona virus pandemic. The detection tool was developed to alert people to keep safe distance among each other by evaluating a video input feed. The video frame from the ‘avi’ file was given as input, and the object detection pre-trained model based on the YOLOv3 algorithm was employed for pedestrian detection. Then, the video frame was transformed into top-down view for distance measurement from the 2D plane. The distance between people can be estimated and any noncompliant pair of people in the display will be indicated with a red frame and red line. The proposed method was validated on a pre-recorded video of pedestrians walking on the street. The output result shows that the proposed method is able to determine the social distancing measures between multiple people in the video. The developed technique can be further developed as a detection tool in real time application. The project is designed using Python 3.5.2 with opencv-python 4.2.0
Keywords: Social Distancing, Pedestrian Detection, Deep Learning, Convolutional Neural Network
Cite Article: "Social Distancing Detection using Deep Learning Model", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.6, Issue 4, page no.426 - 431, April-2021, Available :http://www.ijsdr.org/papers/IJSDR2104069.pdf
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Publication Details: Published Paper ID: IJSDR2104069
Registration ID:193190
Published In: Volume 6 Issue 4, April-2021
DOI (Digital Object Identifier):
Page No: 426 - 431
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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