Age Estimation Using Local Binary Pattern Kernel Density Estimate

  • Juha Ylioinas
  • Abdenour Hadid
  • Xiaopeng Hong
  • Matti Pietikäinen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8156)


We propose a novel kernel method for constructing local binary pattern statistics for facial representation in human age estimation. For age estimation, we make use of the de facto support vector regression technique. The main contributions of our work include (i) evaluation of a pose correction method based on simple image flipping and (ii) a comparison of two local binary pattern based facial representations, namely a spatially enhanced histogram and a novel kernel density estimate. Our single- and cross-database experiments indicate that the kernel density estimate based representation yields better estimation accuracy than the corresponding histogram one, which we regard as a very interesting finding. In overall, the constructed age estimation system provides comparable performance against the state-of-the-art methods. We are using a well-defined evaluation protocol allowing a fair comparison of our results.


Face Recognition Face Image Local Binary Pattern Kernel Density Estimate Facial Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    The FG-NET Aging Database,
  2. 2.
    Gallagher, A.C., Chen, T.: Understanding images of groups of people. In: CVPR 2009, pp. 256–263 (2009)Google Scholar
  3. 3.
    Fu, Y., Guo, G., Huang, T.S.: Age synthesis and estimation via faces: A survey. IEEE TPAMI 32(11), 1955–1976 (2010)CrossRefGoogle Scholar
  4. 4.
    Kwon, H.Y., da Vitoria Lobo, N.: Age classification from facial images. In: CVPR 1994, pp. 762–767 (1994)Google Scholar
  5. 5.
    Lanitis, A., Taylor, C.J., Cootes, T.F.: Toward automatic simulation of aging effects on face images. IEEE TPAMI 24(4), 442–455 (2002)CrossRefGoogle Scholar
  6. 6.
    Guo, G., Mu, G., Fu, Y., Huang, T.S.: Human age estimation using bio-inspired features. In: CVPR 2009, pp. 112–119 (2009)Google Scholar
  7. 7.
    Ruiz, J., Crowley, J., Lux, A.: ”How old are you?”: Age estimation with tensors of binary gaussian receptive maps. In: BMVC 2010, pp. 6.1–6.11 (2010)Google Scholar
  8. 8.
    Gross, R., Baker, S., Matthews, I., Kanade, T.: Face recognition across pose and illumination. In: Li, S.Z., Jain, A.K. (eds.) Handbook of face recognition, pp. 197–221. Springer, London (2011)CrossRefGoogle Scholar
  9. 9.
    Vu, N.-S., Caplier, A.: Face recognition with patterns of oriented edge magnitudes. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part I. LNCS, vol. 6311, pp. 313–326. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  10. 10.
    Guo, Z., Zhang, L., Zhang, D.: A completed modeling of local binary pattern operator for texture classification. IEEE TIP 19(6), 1657–1663 (2010)Google Scholar
  11. 11.
    Ylioinas, J., Hadid, A., Pietikäinen, M.: Age classification in constrained conditions using LBP variants. In: ICPR 2012, pp. 1257–1260 (2012)Google Scholar
  12. 12.
    Ahonen, T., Hadid, A., Pietikäinen, M.: Face description with local binary patterns: Application to face recognition. IEEE TPAMI 28(12), 2037–2041 (2006)CrossRefGoogle Scholar
  13. 13.
    Aitchison, J., Aitken, C.: Multivariate binary discrimination by the kernel method. Biometrika 63(3), 413–420 (1976)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE TPAMI 24(7), 971–987 (2002)CrossRefGoogle Scholar
  15. 15.
    Lanitis, A., Draganova, C., Christodoulou, C.: Comparing different classifiers for automatic age estimation. IEEE TSMCB 34(1), 621–628 (2004)Google Scholar
  16. 16.
    Yan, S., Wang, H., Tang, X., Huang, T.S.: Learning auto-structured regressor from uncertain nonnegative labels. In: ICCV 2007, pp. 1–8 (2007)Google Scholar
  17. 17.
    Yan, S., Wang, H., Tang, X., Liu, J., Huang, T.S.: Regression from uncertain labels and its applications to soft biometrics. IEEE TIFS 3(4), 698–708 (2008)Google Scholar
  18. 18.
    Guo, G., Yun, F., Dyer, C.R., Huang, T.S.: Image-based human age estimation by manifold learning and locally adjusted robust regression. IEEE TIP 17(7), 1178–1188 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Juha Ylioinas
    • 1
  • Abdenour Hadid
    • 1
  • Xiaopeng Hong
    • 1
  • Matti Pietikäinen
    • 1
  1. 1.Center for Machine Vision ResearchUniversity of OuluFinland

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