AccessNet:一种基于三层视觉的禁区访问认证系统

Md. Farukh Hashmi, B. Ashish, Satyarth Katiyar, A. Keskar
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引用次数: 2

摘要

如今,非接触式身份验证已成为一个热门话题,尤其是在这种冠状病毒大流行的情况下,非接触式访问系统是一种预防措施。目前最重要的两种非接触式认证系统是面部识别和步态识别。由于面部识别有可能受到恐怖袭击,步态模式越来越受欢迎,尤其是在高度安全的地区。步态生物识别技术被认为是新一代的生物识别技术,即使在一定距离内也可以识别受试者,避免任何表面接触。然而,复杂挑战步态模式主要是环境设置的视角和距离,以及算法设置的关键步态特征。因此,作者正在扩展他们之前的工作,即根据他们的步态模式在防御应用中识别“特定目标”。我们将面部识别设计与我们的反欺骗算法和步态模式相结合,无论他们的背景,运动和角度如何,平均准确率都达到92%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AccessNet: A Three Layered Visual Based Access Authentication System for Restricted Zones
Contactless authentication has become a trending topic these days, especially in this Corona pandemic situation, where contactless access systems are precautionary steps. The two most important contactless authentication systems right now are facial recognition and gait recognition. With having a possibility of spook attacks on facial recognition, gait patterns have gained popularity especially in the high-secured zones. Gait biometrics is considered as the next generation of biometrics which can enable identification of subjects even through a certain distance, avoiding any surface-contact. However, complex challenges gait patterns are mainly the view angles and distances for environmental setup and crucial gait features for algorithm setup. Hence, the authors are extending their previous work which is identifying ‘specific targets’ based on their gait patterns in Defence applications. We combined facial recognition designed with our anti-spoofing algorithm and gait patterns which gave on an average 92% accuracy irrespective of their background, motion, and angle.
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