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Implementing a Real Time Human Detection and Monitoring Social Distancing for Covid-19 Using V-J algorithm and OpenCV

Journal: International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE) (Vol.10, No. 2)

Publication Date:

Authors : ;

Page : 1340-1345

Keywords : Adaboost; Cascade classifier; Haar-like features; Social Distancing norm; Viola jones;

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Abstract

Recently, the outbreak of Coronavirus Disease (COVID-19) has spread rapidly across the world and thus social distancing has becomeone of mandatory preventive measures to avoid physical contact. COVID-19 is a disease caused by a severe respiratory syndrome coronavirus. The continuous development of technology of IT enabled computers to see and learn. There are many viable applications for computer learning and vision to solve new tasks. In this paper, we propose a framework, able of automatically detect no. of human bodies present in a single image, acquired by a traditional low-cost camera. In this paper Viola jones algorithm is usedto detect human monitoring social distancing norm. System is divided into two parts, the first part is about person detection whereas second part is about monitoring whether people are following social distancing or not, it is applicable if image containsmore than one human. This paper is going to study and understand the Viola-Jones algorithm by implementing the whole detection framework and based on the implementation, conduct experiment to hopefully further improve the performance

Last modified: 2021-04-15 23:22:41