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Using LDP-TOP in video-based spoofing detection

Phan, Quoc Tin, Dang-Nguyen, Duc-Tien ORCID: 0000-0002-2761-2213, Boato, Giulia and De Natale, Francesco (2017) Using LDP-TOP in video-based spoofing detection. In: International Conference on Image Analysis and Processing (ICIAP), 11-15 Sept 2017, Catania, Italy. ISBN 978-3-319-68548-9

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Abstract

Face authentication has been shown to be vulnerable against three main kinds of attacks: print, replay, and 3D mask. Among those, video replay attacks appear more challenging to be detected. There exist in the literature many countermeasures to face spoofing attacks, but a sophisticated detector is still needed to deal with particularly high-quality video based attacks. In this work, we perform analysis on the noise residual in frequency domain, and extract discriminative features by using a dynamic texture descriptor to characterize video based spoofing attacks. We propose a promising detector, which produces competitive results on the most challenging dataset of video based spoofing.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Face Anti-Spoofing; Local Derivative Pattern; Video Based Attacks
Subjects:Computer Science > Computer security
Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: Battiato, Sebastiano and Gallo, Giovanni and Schettini, Raimondo and Stanco, Filippo, (eds.) International Conference on Image Analysis and Processing (ICIAP), Proceedings, Part 2. Lecture Notes in Computer Science book series (LNCS, volume 10485) 10485. Springer. ISBN 978-3-319-68548-9
Publisher:Springer
Official URL:http://dx.doi.org/10.1007/978-3-319-68548-9_56
Copyright Information:© 2017 Springer
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:22035
Deposited On:25 Sep 2017 08:47 by Duc-Tien Dang-Nguyen . Last Modified 08 Nov 2021 14:51

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