An Analysis-by-Synthesis Method for Heterogeneous Face Biometrics

  • Rui Wang
  • Jimei Yang
  • Dong Yi
  • Stan Z. Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

Face images captured in different spectral bands, e.g., in visual (VIS) and near infrared (NIR), are said to be heterogeneous. Although a person’s face looks different in heterogeneous images, it should be classified as being from the same individual. In this paper, we present a new method, called face analogy, in the analysis-by-synthesis framework, for heterogeneous face mapping, that is, transforming face images from one type to another, and thereby performing heterogeneous face matching. Experiments show promising results.

Keywords

Heterogenous face biometrics face analogy face matching analysis-by-synthesis 

References

  1. 1.
    Zhao, W., Chellappa, R., Phillips, P., Rosenfeld, A.: Face recognition: A literature survey. ACM Computing Surveys, 399–458 (2003)Google Scholar
  2. 2.
    Li, S.Z., Chu, R., Liao, S., Zhang., L.: Illumination invariant face recognition using near-infrared images. IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (2007) (Special issue on Biometrics: Progress and Directions)Google Scholar
  3. 3.
    Kong, S.G., Heo, J., Abidi, B., Paik, J., Abidi, M.: Recent advances in visual and infrared face recognition - A review. Computer Vision and Image Understanding 97(1), 103–135 (2005)Google Scholar
  4. 4.
    Bowyer, K.W., Chang, Flynn, P.J.: A survey of 3D and multi-modal 3D+2D face recognition. In: Proceedings of International Conference on Pattern Recognition, pp. 358–361 (2004)Google Scholar
  5. 5.
    Tang, X., Wang, X.: Face sketch recognition. IEEE Transactions on Circuits and Systems for Video Technology 14(1), 50–57 (2004)Google Scholar
  6. 6.
    Yi, D., Liu, R., Chu, R., Lei, Z., Li, S.Z.: Face matching between near infrared and visible light images. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 523–530. Springer, Heidelberg (2007)Google Scholar
  7. 7.
    Yang, W., Yi, D., Lei, Z., Sang, J., Li, S.Z.: 2D-3D face matching using CCA. In: Proc. IEEE International Conference on Automatic Face and Gesture Recognition (2008)Google Scholar
  8. 8.
    Lei, Z., Bai, Q., He, R., Li, S.Z.: Face shape recovery from a single image using cca mapping between tensor spaces. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2008)Google Scholar
  9. 9.
    NIST: Multiple Biometric Grand Challenge (MBGC) (2008), http://face.nist.gov/mbgc
  10. 10.
    Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Salesin, D.H.: Image analogies. In: Fiume, E. (ed.) SIGGRAPH 2001, Computer Graphics Proceedings, pp. 327–340. ACM Press / ACM SIGGRAPH (2001)Google Scholar
  11. 11.
    Xie, X., Lam, K.M.: An efficient illumination normalization method for face recognition. Pattern Recognition Letters 27, 609–617 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Rui Wang
    • 1
  • Jimei Yang
    • 1
  • Dong Yi
    • 1
  • Stan Z. Li
    • 1
  1. 1.Center for Biometrics and Security Research, Institute of AutomationChinese Academy of SciencesBeijingChina

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