Facial Geometry Estimation Using Photometric Stereo and Profile Views

  • Gary A. Atkinson
  • Melvyn L. Smith
  • Lyndon N. Smith
  • Abdul R. Farooq
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)


This paper presents a novel method for estimating the three-dimensional shape of faces, facilitating the possibility of enhanced face recognition. The method involves a combined use of photometric stereo and profile view information. It can be divided into three principal stages: (1) An initial estimate of the face is obtained using four-source high-speed photometric stereo. (2) The profile is determined from a side-view camera. (3) The facial shape estimation is iteratively refined using the profile until an energy functional is minimised. This final stage, which is the most important contribution of the paper, works by continually deforming the shape estimate so that its profile is exact. An energy is then calculated based on the difference between the raw images and synthetic images generated using the new shape estimate. The surface normals are then adjusted according to energy until convergence. Several real face reconstructions are presented and compared to ground truth. The results clearly demonstrate a significant improvement in accuracy compared to standard photometric stereo.


Ground Truth Face Recognition Initial Estimate Face Image Visual Hull 
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.
    Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: A literature survey. ACM Computing Surveys 35, 399–458 (2003)CrossRefGoogle Scholar
  2. 2.
    Zhao, W., Chellappa, R. (eds.): Face Processing: Advanced Modeling and Methods. Elsevier, Amsterdam (2006)Google Scholar
  3. 3.
    Gupta, S., Markey, M.K., Bovik, A.C.: Advances and challenges in 3D and 2D+3D human face recognition. In: Pattern Recognition Theory and Application. Nova Science Publishers, Inc., New York (2008)Google Scholar
  4. 4.
    Lu, X., Colbry, D.: Matching 2.5D face scans to 3D models. IEEE Trans. Patt. Anal. Mach. Intell. 28, 31–43 (2006)Google Scholar
  5. 5.
    Papatheororou, T., Rueckert, D.: Evaluation of automatic 4D face recognition using surface and texture registration. In: Proc. Automatic Face and Gesture Recognition, pp. 321–326 (2004)Google Scholar
  6. 6.
    Blanz, V., Vetter, T.: A morphable model for the synthesis of 3D faces. In: SIGGRAPH, pp. 87–194 (1999)Google Scholar
  7. 7.
    Zhang, R., Tsai, P.S., Cryer, J.E., Shah, M.: Shape from shading: A survey. IEEE Trans. Patt. Anal. Mach. Intell. 21, 690–706 (1999)Google Scholar
  8. 8.
    Woodham, R.J.: Photometric method for determining surface orientation from multiple images. Optical Engineering 19, 139–144 (1980)Google Scholar
  9. 9.
    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 Trans. Patt. Anal. Mach. Intell. 23, 643–660 (2001)Google Scholar
  10. 10.
    Zhao, W.Y., Chellappa, R.: Symmetric shape-from-shading using self ratio image. Intl. J. Comp. Vis. 45, 55–75 (2001)Google Scholar
  11. 11.
    Hernández, C., Vogiatzis, G., Cipolla, R.: Multiview photometric stereo. IEEE Trans. Patt. Anal. Mach. Intell. 30, 548–554 (2008)Google Scholar
  12. 12.
    Nehab, D., Rusinkiewicz, S., Davis, J., Ramamoorthi, R.: Efficiently combining positions and normals for precise 3D geometry. In: Proc. SIGGRAPH, pp. 536–543 (2005)Google Scholar
  13. 13.
    Liu, Y., Schmidt, K.L., Cohn, J.F., Mitra, S.: Facial asymmetry quantification for expression invariant human identification. Comp. Vis. Im. Understanding 91, 138–159 (2003)Google Scholar
  14. 14.
    Lienhart, R., Maydt, J.: An extended set of Haar-like features for rapid object detection. In: IEEE ICIP, pp. 900–903 (2002)Google Scholar
  15. 15.
    Forsyth, D.A., Ponce, J.: Computer Vision, A Modern Approach. Prentice-Hall, Upper Saddle River (2003)Google Scholar
  16. 16.
    Frankot, R.T., Chellappa, R.: A method for enforcing integrability in shape from shading algorithms. IEEE Trans. Patt. Anal. Mach. Intell. 10, 439–451 (1988)Google Scholar
  17. 17.
    Pantic, M., Rothkrantz, J.M.: Facial action recognition for facial expression analysis from static face images. IEEE. Trans. Systems, Man and Cybernetics, Part B 34, 1449–1461 (2004)Google Scholar
  18. 18.
    Mian, A.S., Bennamoun, M., Owens, R.: An efficient multimodal 2D-3D hybrid approach to automatic face recognition. IEEE Trans. Patt. Anal. Mach. Intell. 29, 1927–1943 (2007)Google Scholar
  19. 19.
  20. 20.
    Torrance, K., Sparrow, M.: Theory for off-specular reflection from roughened surfaces. J. Opt. Soc. Am. 57, 1105–1114 (1967)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Gary A. Atkinson
    • 1
  • Melvyn L. Smith
    • 1
  • Lyndon N. Smith
    • 1
  • Abdul R. Farooq
    • 1
  1. 1.University of West EnglandBristolUK

Personalised recommendations