Abstract
On wearable and Virtual Reality (VR) platforms, user authentication is a basic function, but usually a keyboard or touchscreen cannot be provided to type a password. Hand gesture and especially in-air-handwriting can be potentially used for user authentication because a gesture input interface is readily available on these platforms. However, determining whether a login request is from the legitimate user based on a piece of hand movement is challenging in both signal processing and matching, which leads to limited performance in existing systems. In this paper, we propose a multifactor user authentication framework using both the motion signal of a piece of in-air-handwriting and the geometry of hand skeleton captured by a depth camera. To demonstrate this framework, we invented a signal matching algorithm, implemented a prototype, and conducted experiments on a dataset of 100 users collected by us. Our system achieves 0.6% Equal Error Rate (EER) without spoofing attack and 3.4% EER with spoofing only data, which is a significant improvement compared to existing systems using the Dynamic Time Warping (DTW) algorithm. In addition, we presented an in-depth analysis of the utilized features to explain the reason for the performance boost.
Original language | English (US) |
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Title of host publication | Proceedings - 2018 International Conference on Biometrics, ICB 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 255-262 |
Number of pages | 8 |
ISBN (Electronic) | 9781538642856 |
DOIs | |
State | Published - Jul 13 2018 |
Event | 11th IAPR International Conference on Biometrics, ICB 2018 - Gold Coast, Australia Duration: Feb 20 2018 → Feb 23 2018 |
Other
Other | 11th IAPR International Conference on Biometrics, ICB 2018 |
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Country/Territory | Australia |
City | Gold Coast |
Period | 2/20/18 → 2/23/18 |
Keywords
- Hand Geometry
- In Air Handwriting
- User Authentication
ASJC Scopus subject areas
- Instrumentation
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Pathology and Forensic Medicine