To search, Click below search items. |
| All Published Papers Search Service |
|
|
|
Title |
An Approach to Detect Violation of Social Distancing Norms in Public Domain |
|
Author |
M.B.Chandak |
| Citation |
Vol. 25 No. 9 pp. 31-36 |
|
Abstract |
The COVID-19 virus is an ongoing global crisis with more than 247,000 deaths globally. The lack of a vaccine makes precautions against the virus an essential step. One of the best ways to observe these precautions is Social Distancing. This article proposes a deep learning based framework for automating the task of monitoring social distancing using surveillance video, utilizing AWS Object Rekognition for its object detection models to detect humans. Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. Distance is calculated between these objects to find the high-risk rate, low-risk rate and safe distance rate. An analysis of this data is presented. |
|
Keywords |
Social Distancing, Object Detection, Object Tracking, COVID-19, Amazon Rekognition, Video Surveillance |
|
URL |
