Generalized face anti-spoofing by detecting pulse from face videos

Xiaobai Li, Jukka Komulainen, Guoying Zhao*, Pong Chi YUEN, Matti Pietikainen

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

161 Citations (Scopus)


Face biometric systems are vulnerable to spoofing attacks. Such attacks can be performed in many ways, including presenting a falsified image, video or 3D mask of a valid user. A widely used approach for differentiating genuine faces from fake ones has been to capture their inherent differences in (2D or 3D) texture using local descriptors. One limitation of these methods is that they may fail if an unseen attack type, e.g. a highly realistic 3D mask which resembles real skin texture, is used in spoofing. Here we propose a robust anti-spoofing method by detecting pulse from face videos. Based on the fact that a pulse signal exists in a real living face but not in any mask or print material, the method could be a generalized solution for face liveness detection. The proposed method is evaluated first on a 3D mask spoofing database 3DMAD to demonstrate its effectiveness in detecting 3D mask attacks. More importantly, our cross-database experiment with high quality REAL-F masks shows that the pulse based method is able to detect even the previously unseen mask type whereas texture based methods fail to generalize beyond the development data. Finally, we propose a robust cascade system combining two complementary attack-specific spoof detectors, i.e. utilize pulse detection against print attacks and color texture analysis against video attacks.

Original languageEnglish
Title of host publication2016 23rd International Conference on Pattern Recognition, ICPR 2016
Number of pages6
ISBN (Electronic)9781509048472
Publication statusPublished - 1 Jan 2016
Event23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico
Duration: 4 Dec 20168 Dec 2016

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Conference23rd International Conference on Pattern Recognition, ICPR 2016

Scopus Subject Areas

  • Computer Vision and Pattern Recognition

User-Defined Keywords

  • Anti-spoofing
  • Cross-database
  • Face liveness
  • Mask
  • Pulse


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