Detection of face spoofing using visual dynamics

Tirunagari, Santosh, Poh, Norman, Windridge, David, Iorliam, Aamo, Suki, Nik and Ho, Anthony T. S. (2015) Detection of face spoofing using visual dynamics. IEEE Transactions on Information Forensics and Security, 10 (4). pp. 762-777. ISSN 1556-6013 (doi:https://doi.org/10.1109/TIFS.2015.2406533)

[img] PDF - Published version (with publisher's formatting)
Restricted to Repository staff and depositor only

Download (1MB) |

Abstract

Rendering a face recognition system robust is vital in order to safeguard it against spoof attacks carried out by 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 anti-spoofing 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 (LBP), and Support Vector Machines (SVM) 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: print-attack, replay-attack, and CASIA-FASD, attaining comparable results with the state of the art, following the respective published experimental protocols.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 15313
Notes on copyright: Access to full text restricted pending copyright check.
Useful Links:
Depositing User: David Windridge
Date Deposited: 27 Apr 2015 10:13
Last Modified: 31 May 2019 02:45
URI: https://eprints.mdx.ac.uk/id/eprint/15313

Actions (login required)

Edit Item Edit Item

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year