Turnstile Access based on Facial Recognition and Vaccine Passport Verification

S. Aliyeva, Ali Parsayan
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Abstract

This paper aims to provide a system ensuring turnstile access based on facial recognition and vaccine passport verification in order to enable touch-free entrance to buildings, universities, offices, etc. The algorithm of the proposed method is comprised of two essential parts: YOLO algorithm for face detection and CNN for face recognition. After successful user authentication, there are two important criteria that should be met for granting access to the person: Person should not be an active COVID-19 patient and Person should have a valid vaccine passport. The proposed method results 95.57% accuracy rate for face detection with YOLO algorithm and 70% for face recognition with CNN.
基于人脸识别和疫苗护照验证的旋转门通道
本文旨在提供一个基于人脸识别和疫苗护照验证的旋转门门禁系统,以实现建筑物,大学,办公室等的免触摸入口。该方法的算法由两部分组成:用于人脸检测的YOLO算法和用于人脸识别的CNN算法。在用户认证成功后,授予该人员访问权限应满足两个重要标准:该人员应不是活跃的COVID-19患者,并且该人员应持有有效的疫苗护照。YOLO算法的人脸检测准确率为95.57%,CNN算法的人脸识别准确率为70%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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