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Face Anti-spoofing to 3D Masks by Combining Texture and Geometry Features

  • Yan Wang
  • Song Chen
  • Weixin Li
  • Di Huang
  • Yuhong Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)

Abstract

Anti-spoofing has become more important in face recognition systems. This paper proposes a novel approach to resist 3D face mask attacks, which jointly uses texture and shape features. Different from existing methods where depth information by extra equipments is required, we reconstruct geometry cues from RGB images through 3D Morphable Model. The hand-crafted features as well as the deep ones are then extracted to comprehensively represent texture and shape differences between real and fake faces and finally fused for decision making. The experiments are carried out on the 3D-MAD dataset and the competitive results indicate the effectiveness.

Keywords

Face anti-spoofing 3D face reconstruction Deep learning 

Notes

Acknowledgment

This work is supported by the National Natural Science Foundation of China (No. 61673033).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Yan Wang
    • 1
  • Song Chen
    • 1
  • Weixin Li
    • 1
  • Di Huang
    • 1
  • Yuhong Wang
    • 1
  1. 1.IRIP Lab, School of Computer Science and EngineeringBeihang UniversityBeijingChina

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