What Is the Average Human Face?

  • George Mamic
  • Clinton Fookes
  • Sridha Sridharan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)


This paper examines the generation of a generic face model from a moderate sized database. Generic models of a human face have been used in a number of computer vision fields, including reconstruction, active appearance model fitting and face recognition. The model that is constructed in this paper is based upon the mean of the squared errors that are generated by comparing average faces that are calculated from two independent and random samplings of a database of 3D range images. This information is used to determine the average amount of error that is present at given height locations along the generic face based on the number of samples that are considered. These results are then used to sub-region the generic face into areas where the greatest variations occur in the generic face models.


Face Recognition Range Image Face Model Active Appearance Model Average Face 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bowyer, K.C.K.W., Flynn, P.J.: A survey of approaches to three-dimensional face recognition. Technical report, University of Notre Dame (2003)Google Scholar
  2. 2.
    Ypsilos, I.A., Hilton, A., Rowe, S.: Video-rate capture of dynamic face shape and appearance. In: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition (2004)Google Scholar
  3. 3.
    Koterba, S., Baker, S., Matthews, I., Changbo, H., Xiao, J., Cohn, J., Kanade, T.: Multi-view aam fitting and camera calibration. In: Tenth IEEE International Conference on Computer Vision, pp. 511–518 (2005)Google Scholar
  4. 4.
    Blanz, V., Vetter, T.: A morphable model for the synthesis of 3d faces. In: SIGGRAPH (1999)Google Scholar
  5. 5.
    Phillips, J., Flynn, P., Scruggs, T., Bowyer, K., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the face recognition grand challenge. In: Proceedings of IEEE Conference of Computer Vision and Pattern Recognition, vol. 1, pp. 947–954 (2005)Google Scholar
  6. 6.
    Kuo, C., Lin, T.G., Huang, R.S., Odeh, S.: Facial model estimation from stereo/mono image sequence. IEEE Transactions on Multimedia 5(1), 8–23 (2003)CrossRefGoogle Scholar
  7. 7.
    Chen, Q., Medioni, G.: Building 3d human face models from two photographs. Journal of VLSI Signal Processing 27, 127–140 (2001)MATHCrossRefGoogle Scholar
  8. 8.
    Fua, P., Miccio, C.: Animated heads from ordinary images: A least-squares approach. Computer Vision and Image Understanding 75(3), 247–259 (1999)CrossRefGoogle Scholar
  9. 9.
    Choi, K., Worthington, P., Hancock, E.: Estimating facial pose using shape-from-shading. Pattern Recognition Letters 23(5), 533–548 (2002)MATHCrossRefGoogle Scholar
  10. 10.
    Kang, S.: A structure from motion approach using constrained deformable models and apperance prediction. Technical Report CRL 97/6, Cambridge Research Laboratory (1997)Google Scholar
  11. 11.
    Baker, S., Kanade, T.: Super-resolution optical flow. Technical Report CMU-RI-TR-99-36, Robotics Institute, Carnegie Mellon University (1999)Google Scholar
  12. 12.
    Pighin, F., Hecker, J., Lischinski, D., Szeliski, R., Salesin, D.: Synthesizing realistic facial expressions from photographs. In: Proceedings of SIGGRAPH Computer Graphics, vol. 26, pp. 75–84 (1998)Google Scholar
  13. 13.
    Ansari, A.N., Abdel-Mottaleb, M.: 3d face modelling using two views and a generic face model with application to 3d face recognition. In: Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance (2003)Google Scholar
  14. 14.
    DeCarlo, D., Metaxas, D.: Deformable model-based shape and motion analysis from images using motion residual error. In: International Conference on Computer Vision, India, pp. 113–119 (1998)Google Scholar
  15. 15.
    Lengagne, R., Fua, P., Monga, O.: 3d stereo reconstruction of human faces driven by differential constraints. Image and Vision Computing 18, 337–343 (2000)CrossRefGoogle Scholar
  16. 16.
    Blanz, V., Vetter, T.: Face recognition based on fitting a 3d morphable model. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(9), 1063–1074 (2003)CrossRefGoogle Scholar
  17. 17.
    McCool, C., Chandran, V., Sridharan, S.: 2d-3d hybrid face recognition based on pca and feature modelling. In: Proceedings of the 2nd Workshop on Multimodal User Authentication (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • George Mamic
    • 1
  • Clinton Fookes
    • 1
  • Sridha Sridharan
    • 1
  1. 1.Image and Video Research LaboratoryQueensland University of TechnologyBrisbane

Personalised recommendations