Face Recognition from Spatially-Morphed Video Sequences

  • R. Sebastião
  • Jorge A. Silva
  • A. J. Padilha
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4142)


The aim of the present work is the recognition of human face visual information, in order to automatically control the access to restricted areas, granting access to authorized “clients” and barring the entrance to “impostors”. The vision system assembled performed the image acquisition, processing and recognition by first creating a database with a single view of each “client” and then by using multiple test images of each individual candidate to access. To get the test images, a video sequence was captured during the individual’s approach path to the camera. Because subjects presented themselves in a random pose before the camera, the synthesis of frontal views was incorporated, by using a view-morphing method. The modelling and the recognition were handled through the use of ICA methods. The identification of valid “clients” was fully successful. In order to check the rejection of “impostors”, a leave-one-out test was performed which gave promising results.


Face Recognition Video Sequence Test Image Independent Component Analysis Face Image 
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.
    Bartlett, M.S., Movellan, J.R., Sejnowski, T.J.: Face Recognition by Independent Component Analysis. IEEE Transactions on Neural Networks (May 2001)Google Scholar
  2. 2.
    Bartlett, M.S., Lades, H.M., Sejnowski, T.J.: Independent Component Representations for Face Recognition. In: Proceedings of the SPIE Symposium on Electronic Imaging: Science and Technology, San Jose, California, January 1998, vol. 3299, pp. 528–539 (1998)Google Scholar
  3. 3.
    Draper, B.A., et al.: Recognizing faces with PCA and ICA. In: Computer Vision and Image Understanding (to appear, 2003)Google Scholar
  4. 4.
    Hyvärinen, A.: - Survey on Independent Component Analysis. Neural Computing Surveys 2, 94–128 (1999)Google Scholar
  5. 5.
    Hyvärinen, A., Oja, E.: Independent Component Analysis: Algorithms and Applications. Neural Networks 13(4-5), 411–430 (2000)CrossRefGoogle Scholar
  6. 6.
    Hyvärinen, A., Karhunen, J., Oja, E.: Independent Component Analysis, 1st edn. John Wiley & Sons, Inc., New York (2001)CrossRefGoogle Scholar
  7. 7.
    Sebastião, R.: Autenticação de Faces a partir da Aquisição de Sequências de Imagens, MSc thesis, Faculdade de Ciências e Faculdade de Engenharia da Universidade do Porto, Porto (Abril 2004)Google Scholar
  8. 8.
    Seitz, S.M., Dyer, C.R.: View Morphing. In: Proc. SIGGRAPH 1996, pp. 21–30 (1996)Google Scholar
  9. 9.
    Seitz, S.M., Dyer, C.R.: Physically-valid View Synthesis by Image Interpolation. In: Proc. IEEE Workshop on Representations of Visual Scenes, pp. 18–25 (1995)Google Scholar
  10. 10.
    Seitz, Steven Maxwell - Image-Based Transformation of Viewpoint and Scene Appearance, PhD Thesis, University of Wisconsin–Madison, Madison (1997)Google Scholar
  11. 11.
    Torres, L., Lorente, L., Vila, J.: – Automatic Face Recognition of Video Sequences Using Self-eigenfaces. Polytechnic University of Catalonia,
  12. 12.
    Turk, M., Pentland, A.: Eigenfaces for Recognition. Journal of Cognitive Neuroscience 3(1), 71–86 (1991)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • R. Sebastião
    • 1
  • Jorge A. Silva
    • 1
  • A. J. Padilha
    • 1
  1. 1.Faculty of EngineeringUniversity of Porto 

Personalised recommendations