DocumentCode :
49702
Title :
Motion-based counter-measures to photo attacks in face recognition
Author :
Anjos, Andre ; Chakka, Murali Mohan ; Marcel, Sebastien
Author_Institution :
Centre du Parc, Idiap Res. Inst., Martigny, Switzerland
Volume :
3
Issue :
3
fYear :
2014
fDate :
Sept. 2014
Firstpage :
147
Lastpage :
158
Abstract :
Identity spoofing is a contender for high-security face-recognition applications. With the advent of social media and globalised search, peoples face images and videos are wide-spread on the Internet and can be potentially used to attack biometric systems without previous user consent. Yet, research to counter these threats is just on its infancy - the authors lack public standard databases, protocols to measure spoofing vulnerability and baseline methods to detect these attacks. The contributions of this work to the area are 3-fold: first, the authors a publicly available PHOTO-ATTACK database with associated protocols to measure the effectiveness of counter-measures is introduced. Based on the data available, a study is conducted on current state-of-the-art spoofing detection algorithms based on motion analysis, showing they fail under the light of this new dataset. By last, the authors propose a new technique of counter-measure solely based on foreground/background motion correlation using optical flow that outperforms all other algorithms achieving nearly perfect scoring with an equal-error rate of 1.52% on the available test data. The source code leading to the reported results is made available for the replicability of findings in this study.
Keywords :
authorisation; face recognition; image motion analysis; image sequences; background motion correlation; baseline methods; biometric system attack; equal-error rate; face images; face videos; foreground motion correlation; globalised search; high-security face-recognition applications; motion-based photo attack counter-measures; optical flow; public standard databases; publicly available photo-attack database; social media; source code; spooling detection algorithms; spooling vulnerability measurement protocols;
fLanguage :
English
Journal_Title :
Biometrics, IET
Publisher :
iet
ISSN :
2047-4938
Type :
jour
DOI :
10.1049/iet-bmt.2012.0071
Filename :
6887411
Link To Document :
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