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Real-Time Age Estimation from Face Imagery Using Fisher Vectors

  • Lorenzo SeidenariEmail author
  • Alessandro Rozza
  • Alberto Del Bimbo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)

Abstract

In the last decade facial age estimation has grown its importance in computer vision. In this paper we propose an efficient and effective age estimation system from face imagery. To assess the quality of the proposed approach we compare the results obtained by our system with those achieved by other recently published methods on a very large dataset of more than 55K images of people with different gender and ethnicity. These results show how a carefully engineered pipeline of efficient image analysis and pattern recognition techniques leads to state-of-the-art results at 20FPS using a single thread on a 1.6GHZ i5-2467M processor.

Keywords

Age estimation Face analysis Biometrics 

References

  1. 1.
    Cootes, T., Edwards, G., Taylor, C.: Active appearance models. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 681–685 (2001)CrossRefGoogle Scholar
  2. 2.
    Guo, G., Mu, G., Fu, Y., Huang, T.: Human age estimation using bio-inspired features. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 112–119 (2009)Google Scholar
  3. 3.
    Guo, G., Mu, G.: Human age estimation: What is the influence across race and gender? In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 71–78 (2010)Google Scholar
  4. 4.
    Guo, G., Mu, G.: Simultaneous dimensionality reduction and human age estimation via kernel partial least squares regression. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 657–664 (2011)Google Scholar
  5. 5.
    Han, H., Otto, C., Jain, A.K.: Age estimation from face images: Human vs. machine performance. In: International Conference on Biometrics, ICB 2013, June, 4–7, Madrid, Spain (2013)Google Scholar
  6. 6.
    Chang, K.Y., Chen, C.S., Hung, Y.P.: Ordinal hyperplanes ranker with cost sensitivities for age estimation. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 585–592 (2011)Google Scholar
  7. 7.
    Geng, X., Yin, C., Zhou, Z.H.: Facial age estimation by learning from label distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence 35, 2401–2412 (2013)CrossRefGoogle Scholar
  8. 8.
    Snchez, J., Perronnin, F., Mensink, T., Verbeek, J.: Image classification with the fisher vector: Theory and practice. International Journal of Computer Vision 105, 222–245 (2013)Google Scholar
  9. 9.
    Shan, D., Ward, R.: Wavelet-based illumination normalization for face recognition. In: 2005 International Conference on Pattern Recognition (ICPR) (2005)Google Scholar
  10. 10.
    King, D.E.: Max-Margin Object Detection. ArXiv e-prints (2015)Google Scholar
  11. 11.
    Kazemi, V., Sullivan, J.: One millisecond face alignment with an ensemble of regression trees. In: CVPR (2014)Google Scholar
  12. 12.
    Hassner, T., Harel, S., Paz, E., Enbar, R.: Effective face frontalization in unconstrained images. In: Proc. of CVPR (2015)Google Scholar
  13. 13.
    Seidenari, L., Serra, G., Badanov, A.D., Del Bimbo, A.: Local pyramidal descriptors for image recognition. Transactions on Pattern Analisys and Machine Intelligence (2013)Google Scholar
  14. 14.
    Simonyan, K., Parkhi, O.M., Vedaldi, A., Zisserman, A.: Fisher Vector Faces in the Wild. In: British Machine Vision Conference (2013)Google Scholar
  15. 15.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 91–110 (2004)CrossRefGoogle Scholar
  16. 16.
    Akata, Z., Perronnin, F., Harchaoui, Z., Schmid, C.: Good practice in large-scale learning for image classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 36, 507–520 (2014)CrossRefGoogle Scholar
  17. 17.
    Ngan, M., Grother, P.: Face recognition vendor test (frvt) performance of automated age estimation algorithms. Technical report, NIST (2014)Google Scholar
  18. 18.
    Chang, K.Y., Chen, C.S., Hung, Y.P.: A ranking approach for human ages estimation based on face images. In: 2010 20th International Conference on Pattern Recognition (ICPR), pp. 3396–3399 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lorenzo Seidenari
    • 1
    Email author
  • Alessandro Rozza
    • 2
  • Alberto Del Bimbo
    • 1
  1. 1.University of FlorenceFirenzeItaly
  2. 2.Hyera SoftwareCoccaglioItaly

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