Skip to main content

Gender Recognition from a Partial View of the Face Using Local Feature Vectors

  • Conference paper
Pattern Recognition and Image Analysis (IbPRIA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5524))

Included in the following conference series:

Abstract

This paper proposes a gender recognition scheme focused on local appearance-based features to describe the top half of the face. Due to the fact that only the top half of the face is used, this is a feasible approach in those situations where the bottom half is hidden. In the experiments, several face detection methods with different precision levels are used in order to prove the robustness of the scheme with respect to variations in the accuracy level of the face detection process.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Lapedriza, A., Marín-Jiménez, M., Vitrià, J.: Gender recognition in non controlled environments. In: Proc. of 18th ICPR. IEEE, Hong Kong (2006)

    Google Scholar 

  2. Moghaddam, B., Yang, M.: Learning gender with support faces. IEEE Trans. on PAMI 24(5), 707–711 (2002)

    Article  Google Scholar 

  3. Wu, J., Smith, W., Hancock, E.: Learning mixture models for gender classification based on facial surface normals. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds.) IbPRIA 2007. LNCS, vol. 4477, pp. 39–46. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. Burton, A., Bruce, V., Dench, N.: What’s the difference between men and women? evidence from facial measurement. Perception 22(2), 153–176 (1993)

    Article  Google Scholar 

  5. Martínez, A.: Recognizing imprecisely localized, partially occluded and expression variant faces from a single sample per class. IEEE Trans. on PAMI 24(6), 748–763 (2002)

    Article  Google Scholar 

  6. Paredes, R., Pérez-Cortes, J.C., Juan, A., Vidal, E.: Local representations and a direct voting scheme for face recognition. In: PRIS 2001: Proceedings of the 1st International Workshop on Pattern Recognition in Information Systems, pp. 71–79. ICEIS Press (2001)

    Google Scholar 

  7. Phillips, H., Moon, P., Rizvi, S.: The FERET evaluation methodology for face recognition algorithms. IEEE Trans. on PAMI 22(10) (2000)

    Google Scholar 

  8. Nainia, F.B., Mossb, J.P., Gillc, D.S.: The enigma of facial beauty: Esthetics, proportions, deformity, and controversy. American Journal of Orthodontics and Dentofacial Orthopedics 130(3), 277–282 (2006)

    Article  Google Scholar 

  9. Oguz, O.: The proportion of the face in younger adults using the thumb rule of Leonardo da Vinci. Surgical and Radiologic Anatomy 18(2), 111–114 (1996)

    Article  Google Scholar 

  10. Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vision 57(2), 137–154 (2004)

    Article  Google Scholar 

  11. Bradski, G.R., Kaehler, A.: Learning OpenCV. O’Reilly (2008)

    Google Scholar 

  12. Turkowski, K.: Filters for common resampling tasks, 147–165 (1990)

    Google Scholar 

  13. Andreu, Y., Mollineda, R.A.: The role of face parts in gender recognition. In: Campilho, A., Kamel, M.S. (eds.) ICIAR 2008. LNCS, vol. 5112, pp. 945–954. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Andreu, Y., Mollineda, R.A., García-Sevilla, P. (2009). Gender Recognition from a Partial View of the Face Using Local Feature Vectors. In: Araujo, H., Mendonça, A.M., Pinho, A.J., Torres, M.I. (eds) Pattern Recognition and Image Analysis. IbPRIA 2009. Lecture Notes in Computer Science, vol 5524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02172-5_62

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02172-5_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02171-8

  • Online ISBN: 978-3-642-02172-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics