A review of Face Recognition model from video using Deep Learning

Abstract

Recently in covid-19 pandemic different countries has been used AI along with the surveillance technology as a weapon with the battle against Covid-19 all over the globe. In Russia face recognition software is used to uphold lockdown restrictions, In France it’s tested video surveillance cameras whenever lockdown has been directed to make a decision if residents are following the social distancing rules and also check whether they are wearing masks. In china helping to guard transportation system riders by checking commuters for fever before boarding. The technology supplied by Chinese company Hikvision uses a thermal camera that permits temperature readings from a distance of 1.8 meters and, through video analytics, determines whether the person is wearing a mask on face. Just in case of a fever or lack of a mask, the turnstiles won't open. Additionally, the technology can alert a monitoring center if someone has a fever and send along their image, so cases are often tracked. The COVID- 19 pandemic, facial recognition systems joined with other biometric   procedures   produce    a    correct    result. The overall face recognition market is increased from USD

billion in 2020 to USD 4.5 billion by 2021, at a Compound annual rate of growth of 17.1% during the forecast time-frame. This review proposes the foremost significant methods of deep learning used in face recognition. A brief history of face recognition and application