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Face Anti-spoofing Based on Specular Feature Projections

  • Balaji Rao KatikaEmail author
  • Kannan Karthik
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1022)

Abstract

The need for facial anti-spoofing has emerged to counter the usage of facial prosthetics and other forms of spoofing at unmanned surveillance stations. While some part of literature recognizes the difference in texture associated with a prosthetic in comparison with a genuine face, the solutions presented are largely prosthetic model specific and rely on two-sided calibration and training. In this paper, we focus on the specular component associated with genuine faces and claim that on account of the natural depth variation, its feature diversity is expected to be much larger as compared to prosthetics or even printed photo impersonations. In our work concerning one-sided calibration, we first characterize the specular feature space corresponding to genuine images and learn the projections of genuine and spoof data onto this basis. The trained SVM corresponding to genuine projections, 3D mask projections, and printed photo projections is then used as an anti-spoofing model for detecting impersonations.

Keywords

Face Anti-spoofing Specular feature Eigenspace Printed photos 3D Mask Low-rank component Sparse component SVM classifier 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Electronics and Electrical EngineeringIndian Institute of Technology GuwahatiGuwahatiIndia

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