VID: Human identification through vein patterns captured from commodity depth cameras
Author:
Affiliation:
1. School of Computer Science and Engineering The University of New South Wales Randwick New South Wales Australia
2. Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China
Publisher
Institution of Engineering and Technology (IET)
Subject
Computer Vision and Pattern Recognition,Signal Processing,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/bme2.12009
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2. Shah S.W. Kanhere S.S.:Wi‐access: Second factor user authentication leveraging WiFi signals. In:2018 IEEE International Conference on Pervasive Computing and Communications Workshops pp.330–335.PerCom Workshops(2018)
3. Wifi‐id: Human identification using wifi signal;Zhang J.;In: DCOSS, Washington, DC., 26 ‐ 28 May,2016
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