Liveness Detection Using Implicit 3D Features

J. Matias Di Martino; Qiang Qiu; Trishul Nagenalli; Guillermo Sapiro

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arXiv · 1804.06702

Liveness Detection Using Implicit 3D Features

J. Matias Di Martino·Qiang Qiu·Trishul Nagenalli·Guillermo Sapiro

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Abstract

Spoofing attacks are a threat to modern face recognition systems. In this work we present a simple yet effective liveness detection approach to enhance 2D face recognition methods and make them robust against spoofing attacks. We show that the risk to spoofing attacks can be re- duced through the use of an additional source of light, for example a flash. From a pair of input images taken under different illumination, we define discriminative features that implicitly contain facial three-dimensional in- formation. Furthermore, we show that when multiple sources of light are considered, we are able to validate which one has been activated. This makes possible the design of a highly secure active-light authentication framework. Finally, further investigating the use of 3D features without 3D reconstruction, we introduce an approximated disparity-based implicit 3D feature obtained from an uncalibrated stereo-pair of cameras. Valida- tion experiments show that the proposed methods produce state-of-the-art results in challenging scenarios with nearly no feature extraction latency.

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BibTeX RIS

J. Matias Di Martino, Qiang Qiu, Trishul Nagenalli, Guillermo Sapiro. 2018-04-19. Liveness Detection Using Implicit 3D Features. https://arxiv.org/abs/1804.06702

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