Skip to main content
SpringerLink
Log in

Dual Camera Based Feature for Face Spoofing Detection

  • Conference paper
  • First Online:
Pattern Recognition (CCPR 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 662))

Included in the following conference series:

Abstract

This paper presents a fused feature using dual cameras for face spoofing detection. The feature takes full advantage of input image pairs in terms of texture and depth. It consists of two parts: 2D component and 3D component. For the former, we propose an algorithm based on image similarity to combine every pair of input images into one gray-level image, from which the 2D feature is extracted. For the latter, based on point feature histograms (PFH) method, we describe the point cloud obtained by stereo reconstruction algorithms. The concatenation of 2D and 3D features above is used to represent the input image pair. Experiments on self collected dataset demonstrate the competitive performance and potential of the proposed feature.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. ISO/IEC 30107–3 Biometric presentation attack detection - part 3: testing and reporting. International Organization for Standardization (2015)

    Google Scholar 

  2. Arashloo, S.R., Kittler, J., Christmas, W.: Face spoofing detection based on multiple descriptor fusion using multiscale dynamic binarized statistical image features. IEEE Trans. Inf. Forensics Secur. 10, 2396–2407 (2015)

    Article  Google Scholar 

  3. Bao, W., Li, H., Li, N., Jiang, W.: A liveness detection method for face recognition based on optical flow field. In: International Conference on Image Analysis and Signal Processing, pp. 233–236. IEEE (2009)

    Google Scholar 

  4. Calonder, M., Lepetit, V., Strecha, C., Fua, P.: BRIEF: binary robust independent elementary features. In: Maragos, P., Paragios, N., Daniilidis, K. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 778–792. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  5. Choudhury, T., Clarkson, B., Jebara, T., Pentland, A.: Multimodal person recognition using unconstrained audio and video. In: International Conference on Audio-and Video-Based Person Authentication, pp. 176–181. Citeseer (1999)

    Google Scholar 

  6. De Marsico, M., Nappi, M., Riccio, D., Dugelay, J.L.: Moving face spoofing detection via 3D projective invariants. In: IAPR International Conference on Biometrics, pp. 73–78. IEEE (2012)

    Google Scholar 

  7. Erdogmus, N., Marcel, S.: Spoofing in 2D face recognition with 3D masks and anti-spoofing with kinect. In: International Conference on Biometrics: Theory, Applications and Systems, pp. 1–6. IEEE (2013)

    Google Scholar 

  8. Gragnaniello, D., Poggi, G., Sansone, C., Verdoliva, L.: An investigation of local descriptors for biometric spoofing detection. IEEE Trans. Inf. Forensics Secur. 10(4), 849–863 (2015)

    Article  Google Scholar 

  9. Kollreider, K., Fronthaler, H., Bigun, J.: Evaluating liveness by face images and the structure tensor. In: Workshop on Automatic Identification Advanced Technologies, pp. 75–80. IEEE (2005)

    Google Scholar 

  10. Li, Q., Xia, Z., Xing, G.: A binocular framework for face liveness verification under unconstrained localization. In: International Conference on Machine Learning and Applications, pp. 204–207. IEEE (2010)

    Google Scholar 

  11. Liu, C., Wechsler, H.: Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition. IEEE Trans. Image Process. 11, 467–476 (2002)

    Article  Google Scholar 

  12. Nosaka, R., Ohkawa, Y., Fukui, K.: Feature extraction based on co-occurrence of adjacent local binary patterns. In: Ho, Y.-S. (ed.) PSIVT 2011, Part II. LNCS, vol. 7088, pp. 82–91. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  13. Pan, G., Sun, L., Wu, Z., Wang, Y.: Monocular camera-based face liveness detection by combining eyeblink and scene context. Telecommun. Syst. 47, 215–225 (2011)

    Article  Google Scholar 

  14. Pinto, A., Pedrini, H., Robson Schwartz, W., Rocha, A.: Face spoofing detection through visual codebooks of spectral temporal cubes. IEEE Trans. Image Process. 24(12), 4726–4740 (2015)

    Article  MathSciNet  Google Scholar 

  15. Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to SIFT or SURF. In: International Conference on Computer Vision, pp. 2564–2571. IEEE (2011)

    Google Scholar 

  16. Rusu, R.B., Blodow, N., Beetz, M.: Fast point feature histograms (FPFH) for 3D registration. In: International Conference on Robotics and Automation, pp. 3212–3217. IEEE (2009)

    Google Scholar 

  17. Rusu, R.B., Blodow, N., Marton, Z.C., Beetz, M.: Aligning point cloud views using persistent feature histograms. In: International Conference on Intelligent Robots and Systems, pp. 3384–3391. IEEE (2008)

    Google Scholar 

  18. Tan, X., Li, Y., Liu, J., Jiang, L.: Face liveness detection from a single image with sparse low rank bilinear discriminative model. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part VI. LNCS, vol. 6316, pp. 504–517. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  19. Wang, T., Yang, J., Lei, Z., Liao, S., Li, S.Z.: Face liveness detection using 3D structure recovered from a single camera. In: International Conference on Biometrics, pp. 1–6. IEEE (2013)

    Google Scholar 

  20. Wen, D., Han, H., Jain, A.K.: Face spoof detection with image distortion analysis. IEEE Trans. Inf. Forensics Secur. 10, 746–761 (2015)

    Article  Google Scholar 

  21. Xiong, X., De la Torre, F.: Supervised descent method and its applications to face alignment. In: Computer Vision and Pattern Recognition, pp. 532–539. IEEE (2013)

    Google Scholar 

  22. Yan, J., Zhang, Z., Lei, Z., Yi, D., Li, S.Z.: Face liveness detection by exploring multiple scenic clues. In: International Conference on Control Automation Robotics and Vision, pp. 188–193. IEEE (2012)

    Google Scholar 

  23. Yang, J., Lei, Z., Liao, S., Li, S.Z.: Face liveness detection with component dependent descriptor. In: 2013 International Conference on Biometrics (ICB), pp. 1–6. IEEE (2013)

    Google Scholar 

  24. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1330–1334 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing, 100190, China

    Xudong Sun, Lei Huang & Changping Liu

Authors
  1. Xudong Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lei Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Changping Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xudong Sun .

Editor information

Editors and Affiliations

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

    Tieniu Tan

  2. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China

    Xuelong Li

  3. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Xilin Chen

  4. Tsinghua University , Beijing, China

    Jie Zhou

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  6. University of Electronic Science and Technology, Chengdu, Sichuan, China

    Hong Cheng

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Sun, X., Huang, L., Liu, C. (2016). Dual Camera Based Feature for Face Spoofing Detection. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-10-3002-4_28

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3002-4_28

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3001-7

  • Online ISBN: 978-981-10-3002-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation