Recent Progress on Face Presentation Attack Detection of 3D Mask Attacks

Si-Qi Liu, Pong C. Yuen*, Xiaobai Li, Guoying Zhao

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingChapterpeer-review

4 Citations (Scopus)

Abstract

With the advanced 3D reconstruction and printing technologies, creating a super-real 3D facial mask becomes feasible at an affordable cost. This brings a new challenge to face presentation attack detection (PAD) against 3D facial mask attack. As such, there is an urgent need to solve this problem as many face recognition systems have been deployed in real-world applications. Since this is a relatively new research problem, few studies has been conducted and reported. In order to attract more attentions on 3D mask face PAD, this book chapter summarizes the progress in the past few years, as well as publicly available datasets. Finally, some open problems in 3D mask attack are discussed.
Original languageEnglish
Title of host publicationHandbook of Biometric Anti-Spoofing
Subtitle of host publicationPresentation Attack Detection
EditorsSébastien Marcel, Mark S. Nixon, Julian Fierrez, Nicholas Evans
Place of PublicationSwitzerland
PublisherSpringer Nature Switzerland AG
Chapter11
Pages229-246
Number of pages18
Edition2nd
ISBN (Electronic)9783319926278
ISBN (Print)9783319926261
DOIs
Publication statusPublished - 2 Jan 2019

Publication series

NameAdvances in Computer Vision and Pattern Recognition
ISSN (Print)2191-6586
ISSN (Electronic)2191-6594

Scopus Subject Areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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