University of Oulu

Z. Boulkenafet, J. Komulainen and A. Hadid, "Face Antispoofing Using Speeded-Up Robust Features and Fisher Vector Encoding," in IEEE Signal Processing Letters, vol. 24, no. 2, pp. 141-145, Feb. 2017. doi: 10.1109/LSP.2016.2630740

Face antispoofing using speeded-up robust features and Fisher vector encoding

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Author: Boulkenafet, Zinelabidine1; Komulainen, Jukka1; Hadid, Abdenour1
Organizations: 1Center for Machine Vision and Signal Analysis, Uni- versity of Oulu, Oulu 90014, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2019-09-13


The vulnerabilities of face biometric authentication systems to spoofing attacks have received a significant attention during the recent years. Some of the proposed countermeasures have achieved impressive results when evaluated on intratests, i.e., the system is trained and tested on the same database. Unfortunately, most of these techniques fail to generalize well to unseen attacks, e.g., when the system is trained on one database and then evaluated on another database. This is a major concern in biometric antispoofing research that is mostly overlooked. In this letter, we propose a novel solution based on describing the facial appearance by applying Fisher vector encoding on speeded-up robust features extracted from different color spaces. The evaluation of our countermeasure on three challenging benchmark face-spoofing databases, namely the CASIA face antispoofing database, the replay-attack database, and MSU mobile face spoof database, showed excellent and stable performance across all the three datasets. Most importantly, in interdatabase tests, our proposed approach outperforms the state of the art and yields very promising generalization capabilities, even when only limited training data are used.

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Series: IEEE signal processing letters
ISSN: 1070-9908
ISSN-E: 1558-2361
ISSN-L: 1070-9908
Volume: 24
Issue: 2
Pages: 141 - 145
DOI: 10.1109/LSP.2016.2630740
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
113 Computer and information sciences
Funding: This was supported in part by the Academy of Finland and in part by the Infotech Oulu.
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