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Using LDP-TOP in video-based spoofing detection

Phan, Quoc Tin, Dang-Nguyen, Duc-Tien orcid logoORCID: 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

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.
Metadata
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, Gallo, Giovanni, 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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