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Remote Identity Verification Using Gait Analysis and Face Recognition
Wireless Communications and Mobile Computing ( IF 2.146 ) Pub Date : 2020-11-23 , DOI: 10.1155/2020/8815461
Wen Si 1, 2 , Jing Zhang 1 , Yu-Dong Li 1 , Wei Tan 3 , Yi-Fan Shao 4 , Ge-Lan Yang 5
Affiliation  

Biometric identification has verified its effectiveness in personal identity verification because of the uniqueness and noninvasion. In this research, we tend to apply the detection of biometric information to a remote sensing system for the purpose of security area monitoring. Our system is established by collecting signals from the coming individuals via the remote measurement in the specific condition where both kinds of data are detected to determine the identity. Specifically, the measuring of gait signals and facial images is integrated to provide a way of improving the detection accuracy and the robustness. In addition, the fuzzy association rule (FAR) is employed for data analysis in line with the outcomes of different methods. As such, the signals are integrated and transmitted for further processing and remote identification. Experiments are conducted to demonstrate the capability of the proposed system. With the training data increases, a high detection accuracy of 95.2% is obtained, which makes it a promising basis for the realization of remote identity verification.

中文翻译:

使用步态分析和面部识别进行远程身份验证

由于其独特性和非侵入性,生物特征识别已验证了其在个人身份验证中的有效性。在这项研究中,我们倾向于将生物特征信息的检测应用于遥感系统,以进行安全区域监视。我们的系统是通过在特定条件下通过远程测量收集来自即将到来的个人的信号而建立的,在特定条件下会同时检测两种数据以确定身份。具体地,步态信号和面部图像的测量被集成以提供提高检测精度和鲁棒性的方式。此外,根据不同方法的结果,采用模糊关联规则(FAR)进行数据分析。这样,信号被集成并传输以用于进一步处理和远程识别。进行实验以证明所提出系统的功能。随着训练数据的增加,获得了95.2%的高检测精度,这为实现远程身份验证提供了有希望的基础。
更新日期:2020-11-23
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