Improved Detection of Face Presentation Attacks Using Image Decomposition

Presentation attack detection (PAD) is a critical component in secure face authentication. We present a PAD algorithm to distinguish face spoofs generated by a photograph of a subject from live images. Our method uses an image decomposition network to extract albedo and normal. The domain gap betwee...

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Bibliographic Details
Published inarXiv.org
Main Authors Mishra, Shlok Kumar, Sengupta, Kuntal, Horowitz-Gelb, Max, Wen-Sheng, Chu, Bouaziz, Sofien, Jacobs, David
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 22.03.2021
Subjects
Albedo
Algorithms
Authentication
Critical components
Decomposition
Domains
Empirical analysis
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ISSN2331-8422

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Summary:Presentation attack detection (PAD) is a critical component in secure face authentication. We present a PAD algorithm to distinguish face spoofs generated by a photograph of a subject from live images. Our method uses an image decomposition network to extract albedo and normal. The domain gap between the real and spoof face images leads to easily identifiable differences, especially between the recovered albedo maps. We enhance this domain gap by retraining existing methods using supervised contrastive loss. We present empirical and theoretical analysis that demonstrates that the contrast and lighting effects can play a significant role in PAD; these show up particularly in the recovered albedo. Finally, we demonstrate that by combining all of these methods we achieve state-of-the-art results on datasets such as CelebA-Spoof, OULU and CASIA-SURF.
Bibliography:content type line 50
SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
ISSN:2331-8422