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Chinese Conference on Biometric Recognition

CCBR 2017: Biometric Recognition pp 108–117Cite as

One-Snapshot Face Anti-spoofing Using a Light Field Camera

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10568))

Abstract

Face recognition is an increasingly popular technology for user authentication. However, face recognition is susceptible to spoofing attacks. Therefore, a reliable way to detect malicious attacks is crucial to the robustness of the face recognition system. This paper describes a new approach to utilizing light field camera for defending spoofing face attacks, like (warped) printed 2D facial photos and high-definition tablet images. The light field camera is a sensor that can record the directions as well as the colors of incident rays. Needing only one snapshot, multiple refocused images can be generated. In the proposed method, three kinds of features extracted from a pair of refocused images are extracted to discriminate fake faces and real faces. To verify the performance, we build a light field photograph databases and conduct experiments. Experimental results reveal that the employed features can achieve remarkable anti-spoofing accuracy under different types of spoofing attacks.

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Notes

  1. 1.

    Available online: https://www.lytro.com/.

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Acknowledgment

We would like to thank Ms. Yun Lei and Mr. Xiya Jia who have made important contributions to this project. This project is supported by the Natural Science Foundation of China (No. 61672544), Guangdong Natural Science Foundation (No. 2015A030311047), Guangzhou Project (No. 201604046018), Fundamental Research Funds for the Central Universities (No. 161gpy41), Shenzhen Innovation Program (No. JCYJ20150401145529008), and Tip-top Scientific and Technical Innovative Youth Talents of Guangdong special support program (No. 2016TQ03X263).

Author information

Authors and Affiliations

  1. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China

    Xiaohua Xie, Yan Gao, Wei-Shi Zheng, Jianhuang Lai & Junyong Zhu

  2. Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou, China

    Xiaohua Xie, Yan Gao, Wei-Shi Zheng, Jianhuang Lai & Junyong Zhu

  3. Key Laboratory of Machine Intelligence and Advanced Computing, Ministry of Education, Sun Yat-sen University, Guangzhou, China

    Xiaohua Xie, Yan Gao, Wei-Shi Zheng, Jianhuang Lai & Junyong Zhu

Authors
  1. Xiaohua Xie
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  2. Yan Gao
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  3. Wei-Shi Zheng
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  4. Jianhuang Lai
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  5. Junyong Zhu
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Corresponding author

Correspondence to Jianhuang Lai .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Computing and Technology, Chinese Academy of Sciences, Beijing, China

    Yong Xu

  5. Shenzhen University, Shenzhen, China

    Linlin Shen

  6. Tsinghua University, Beijing, China

    Jianjiang Feng

  7. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  8. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yu Qiao

  9. Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Zhenhua Guo

  10. Shenzhen University, Shenzhen, China

    Shiqi Yu

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Cite this paper

Xie, X., Gao, Y., Zheng, WS., Lai, J., Zhu, J. (2017). One-Snapshot Face Anti-spoofing Using a Light Field Camera. In: Zhou, J., et al. Biometric Recognition. CCBR 2017. Lecture Notes in Computer Science(), vol 10568. Springer, Cham. https://doi.org/10.1007/978-3-319-69923-3_12

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  • DOI: https://doi.org/10.1007/978-3-319-69923-3_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69922-6

  • Online ISBN: 978-3-319-69923-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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