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Biometric Presentation Attack Detection using Gaze Alignment

Alsufyani, Nawal, Ali, Asad, Hoque, Sanaul, Deravi, Farzin (2018) Biometric Presentation Attack Detection using Gaze Alignment. In: Identity, Security, and Behavior Analysis (ISBA), 2018 IEEE 4th International Conference on. . IEEE ISBN 978-1-5386-2249-0. E-ISBN 978-1-5386-2248-3. (doi:10.1109/ISBA.2018.8311472) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:66578)

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https://dx.doi.org/10.1109/ISBA.2018.8311472

Abstract

Face recognition systems have been improved rapidly in recent decades. However, their wide deployment has been hindered by their vulnerability to spoofing attacks. In this paper, we present a challenge and response method to detect attack in face recognition systems by recording the gaze of a user in response to a moving stimulus. The proposed system extracts eye centres in the captured frames and computes features from these landmarks to ascertain whether the gaze aligns with the challenge trajectory in order to detect spoofing attacks. The system is tested using a new database simulating mobile device use with 70 subjects attempting three types of spoof attacks (projected photo, looking through a 2D mask or wearing a 3D mask). Evaluations on the collected database show that the proposed approach performs favourably when compared with state-of-the-art methods.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/ISBA.2018.8311472
Uncontrolled keywords: face; feature extraction; three-dimensional displays; trajectory; face recognition; databases; two dimensonal displays
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Sanaul Hoque
Date Deposited: 29 Mar 2018 10:55 UTC
Last Modified: 04 Mar 2024 16:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/66578 (The current URI for this page, for reference purposes)

University of Kent Author Information

Alsufyani, Nawal.

Creator's ORCID:
CReDIT Contributor Roles:

Ali, Asad.

Creator's ORCID:
CReDIT Contributor Roles:

Hoque, Sanaul.

Creator's ORCID: https://orcid.org/0000-0001-8627-3429
CReDIT Contributor Roles:

Deravi, Farzin.

Creator's ORCID: https://orcid.org/0000-0003-0885-437X
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