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Detection of face spoofing using visual dynamics

Tirunagari, S, Poh, N, Windridge, D, Iorliam, A, Suki, N and Ho, ATS (2015) Detection of face spoofing using visual dynamics IEEE Transactions on Information Forensics and Security, 10 (4). pp. 762-777.

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© 2015 IEEE.Rendering a face recognition system robust is vital in order to safeguard it against spoof attacks carried out using printed pictures of a victim (also known as print attack) or a replayed video of the person (replay attack). A key property in distinguishing a live, valid access from printed media or replayed videos is by exploiting the information dynamics of the video content, such as blinking eyes, moving lips, and facial dynamics. We advance the state of the art in facial antispoofing by applying a recently developed algorithm called dynamic mode decomposition (DMD) as a general purpose, entirely data-driven approach to capture the above liveness cues. We propose a classification pipeline consisting of DMD, local binary patterns (LBPs), and support vector machines (SVMs) with a histogram intersection kernel. A unique property of DMD is its ability to conveniently represent the temporal information of the entire video as a single image with the same dimensions as those images contained in the video. The pipeline of DMD + LBP + SVM proves to be efficient, convenient to use, and effective. In fact only the spatial configuration for LBP needs to be tuned. The effectiveness of the methodology was demonstrated using three publicly available databases: 1) print-attack; 2) replay-attack; and 3) CASIA-FASD, attaining comparable results with the state of the art, following the respective published experimental protocols.

Item Type: Article
Subjects : Computer Science
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
Tirunagari, S
Poh, N
Windridge, D
Iorliam, A
Suki, N
Date : 1 April 2015
DOI : 10.1109/TIFS.2015.2406533
Copyright Disclaimer : Copyright 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
Depositing User : Symplectic Elements
Date Deposited : 20 Oct 2016 08:24
Last Modified : 31 Oct 2017 18:48

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