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Low rank analysis of eye image sequence– A novel basis for face liveness detection

  • Chengyan Lin
  • , Yuwu Lu
  • , Jian Wu
  • , Yong Xu*
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The security of the face recognition technology has attracted more and more attention because of the wide applications of this technology. A lot of studies on face liveness detection have been performed. In this paper, we cast the face liveness detection problem as a classification problem to distinguish the images of true faces and photo samples based on the rank analysis of sample matrices. We assume that the rank of the true face sample matrix is much higher than that of the photo sample matrix under an ideal situation. If we denoise the real world samples and convert them into pure samples, we can find a well boundary, that is, a basis for liveness detection. Experiments are conducted on the NUAA imposter database to verify the efficiency of the proposed method.

Original languageEnglish
Title of host publicationBiometric Recognition - 10th Chinese Conference, CCBR 2015, Proceedings
EditorsJucheng Yang, Zhenan Sun, Shiguang Shan, Jinfeng Yang, Jianjiang Feng, Weishi Zheng
PublisherSpringer Verlag
Pages11-18
Number of pages8
ISBN (Print)9783319254166
DOIs
StatePublished - 2015
Externally publishedYes
Event10th Chinese Conference on Biometric Recognition, CCBR 2015 - Tianjin, China
Duration: 13 Nov 201515 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9428
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th Chinese Conference on Biometric Recognition, CCBR 2015
Country/TerritoryChina
CityTianjin
Period13/11/1515/11/15

Keywords

  • Classification basis
  • Eye sequence
  • Face liveness
  • Low rank

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