Skip to main content

Asymmetric Facial Shape Based on Symmetry Assumption

  • Conference paper
Biometric Recognition (CCBR 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7098))

Included in the following conference series:

Abstract

It has been known that it is hard to capture the high-frequency components (shadows and specularities) during the modeling of illumination effects. In this paper, we propose a reflectance model to simulate the interaction of light and the facial surface under the assumption that face is strictly axial symmetry. This model works well not only in fitting the intensities of pixel but also in processing the DC component contained in the image. To compute a facial 3D shape, we first augment the input images to get a symmetric facial normal field, then propose a method to obtain a more accurate normal field, and finally compute an integrable shape using the field. Experimental results for face relighting, facial shape recovery demonstrate the effectiveness of our method.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

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.

Similar content being viewed by others

References

  1. Georghiades, A.S., Belhumeur, P.N., Kriegman, D.J.: From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 643–660 (2001)

    Google Scholar 

  2. Basri, R., Jacobs, D.W.: Lambertian Reflectance and Linear Subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 218–233 (2003)

    Google Scholar 

  3. Kemelmacher-Shlizerman, I., Basri, R.: 3D Face Reconstruction from a Single Image Using a Single Reference Face Shape. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 394–405 (2011)

    Google Scholar 

  4. Kumar, R., Barmpoutis, A., Banerjee, A., Vemuri, B.C.: Non-Lambertian Reflectance Modeling and Shape Recovery of Faces Using Tensor Splines. IEEE Transactions on Pattern Analysis and Machine Intelligence 33, 553–566 (2011)

    Google Scholar 

  5. Frankot, R.T., Chellappa, R.: A Method for Enforcing Integrability in Shape from Shading Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 10, 439–451 (1988)

    Google Scholar 

  6. Nilsson, M., Dahl, M., Claesson, I.: The Successive Mean Quantization Transform. In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2005. Proceedings(ICASSP 2005), vol. 4, pp. 429–432 (2005)

    Google Scholar 

  7. Zhao, W.Y., Chellappa, R.: Symmetric Shape-from-Shading Using Self-ratio Image. International Journal of Computer Vision 45, 55–75 (2001)

    Google Scholar 

  8. Kovesi, P.: Shapelets Correlated with Surface Normals Produce Surfaces. In: Tenth IEEE International Conference on Computer Vision (ICCV 2005), vol. 2, pp. 994–1001 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hu, J., Feng, G., Lai, J., Zheng, WS. (2011). Asymmetric Facial Shape Based on Symmetry Assumption. In: Sun, Z., Lai, J., Chen, X., Tan, T. (eds) Biometric Recognition. CCBR 2011. Lecture Notes in Computer Science, vol 7098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25449-9_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25449-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25448-2

  • Online ISBN: 978-3-642-25449-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics