Blinking-Based Live Face Detection Using Conditional Random Fields

  • Lin Sun
  • Gang Pan
  • Zhaohui Wu
  • Shihong Lao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)


This paper presents a blinking-based liveness detection method for human face using Conditional Random Fields (CRFs). Our method only needs a web camera for capturing video clips. Blinking clue is a passive action and does not need the user to to any hint, such as speaking, face moving. We model blinking activity by CRFs, which accommodates long-range contextual dependencies among the observation sequence. The experimental results demonstrate that the proposed method is promising, and outperforms the cascaded Adaboost method and HMM method.


  1. 1.
    Jain, A., Bolle, R., Pankanti, S.: Personal Identification in Networked Society. Springer, Heidelberg (1999)Google Scholar
  2. 2.
    Robert, W.F., Ulrich, D.: BioID: A Multimodal Biometric Identification System. IEEE Computer 33(2), 64–68 (2000)Google Scholar
  3. 3.
    Choudhury, T., Clarkson, B., Jebara, T., Pentland, A.: Multimodal person recognition using unconstrained audio and video. In: Proc. 2nd Int. Conf. Audio-Video Based Person Authentication, pp. 176–181 (1999)Google Scholar
  4. 4.
    Li, J.W., Wang, Y.H., Tan, T.N., Jain, A.K.: Live Face Detection Based on the Analysis of Fourier Spectra. In: Proc. SPIE. Biometric Technology for Human Identification, vol. 5404, pp. 296–303 (2004)Google Scholar
  5. 5.
    Kollreider, K., Fronthaller, H., Bigun, J.: Evaluating liveness by face images and the structure tensor. AutoID (2005)Google Scholar
  6. 6.
    Moriyama, T., Kanade, T., Cohn, J.F., Xiao, J., Ambadar, Z., Gao, J., Imamura, H.: Automatic Recognition of Eye Blinking in Spontaneously Occurring Behavior. In: Proc. Int. Conf. on Pattern Recognition, vol. 4, pp. 78–81 (2002)Google Scholar
  7. 7.
    Lafferty, J., McCallum, A., Pereira, F.: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In: Proc. 18th Int. Conf. Machine Learning, pp. 282–289 (2001)Google Scholar
  8. 8.
    Sha, F., Pereira, F.: Shallow Parsing with Conditional Random Fields. Proc. Human Language Technology, NAACL, 213–220 (2003)Google Scholar
  9. 9.
    McCallum, A.: Efficiently Inducing Features of Conditional Random Fields. In: Proc. 19th Uncertainty in Artificial Intelligence, pp. 403–410 (2003)Google Scholar
  10. 10.
    Hammersley, J., Clifford, P.: Markov fields on finite graphs and lattices (Unpublished manuscript 1971)Google Scholar
  11. 11.
    Lienhart, R., Kuranov, A., Pisarevsky, V.: Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection. In: Proc. 25th German Pattern Recognition Symposium, pp. 297–304 (2003)Google Scholar
  12. 12.
    Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences 55(1), 119–139 (1997)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Rabiner, L.: A tutorial on hidden markov models and selected applications in speech recognition. Proc. IEEE (1989)Google Scholar
  14. 14.
    Cristian, S., Kanaujia, A., Li, Z.G., Metaxas, D.: Conditional Models for Contextual Human Motion Recognition. In: Proc. Int. Conf. Computer Vision, pp. 1808–1815 (2005)Google Scholar
  15. 15.
    Bobick, A., Davis, J.: The recognition of human movement using temporal templates. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 928–934 (2001)Google Scholar
  16. 16.
    Gavrila, D.: The Visual Analysis of Human Movement: A Survey. Computer Vision and Image Understanding 73(1), 82–98 (1999)zbMATHCrossRefGoogle Scholar
  17. 17.
    Viola, P., Jones, M.J.: Rapid Object Detection using a Boosted Cascade of Simple Features. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 511–518 (2001)Google Scholar
  18. 18.
    Phillips, P.J., Moon, H., Rauss, P.J., Rizvi, S.: The FERET Evaluation Methodology for Face-Recognition Algorithms. IEEE Trans. Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000)CrossRefGoogle Scholar
  19. 19.
    Hyoja-Dong, Nam-Gu: Asian Face Image Database PF01. Technical Report, Pohang University of Science and Technology
  20. 20.
    Zhang, X.H., Shan, S.G., Cao, B., Gao, W., Zhou, D.L., Zhao, D.B.: CAS-PEAL: A Large-Scale Chinese Face Database and Some Primary Evaluations (in Chinese). Journal of Computer-Aided Design and Computer Graphics 17(1), 9–17 (2005)Google Scholar
  21. 21.
    Karson, C.N.: Spontaneous eye-blink rates and dopaminergic systems. Brain 106, 643–653 (1983)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Lin Sun
    • 1
  • Gang Pan
    • 1
  • Zhaohui Wu
    • 1
  • Shihong Lao
    • 2
  1. 1.Dept. of Computer Science, Zhejiang University, HangzhouP.R. China
  2. 2.Sensing and Control Technology Laboratory, OMRON CorporationJapan

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