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Plenoptic Face Presentation Attack Detection

  • Shuaishuai Zhu*
  • , Xiaobo Lv
  • , Xiaohua Feng
  • , Jie Lin
  • , Peng Jin
  • , Liang Gao
  • *Corresponding author for this work
  • University of Illinois at Urbana-Champaign
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

The vulnerability of current face recognition systems to presentation attacks significantly limits their application in biometrics. Herein, we present a passive presentation attack detection method based on a complete plenoptic imaging system which can derive the complete plenoptic function of light rays using a single detector. Moreover, we constructed a multi-dimensional face database with 50 subjects and seven different types of presentation attacks. We experimentally demonstrated that our approach outperforms the state-of-the-art methods on all types of presentation attacks.

Original languageEnglish
Article number9035405
Pages (from-to)59007-59014
Number of pages8
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

Keywords

  • Biometrics
  • face recognition
  • light-field imaging
  • multi-spectral imaging

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