Face Shape Recovery and Recognition Using a Surface Gradient Based Statistical Model

  • Mario Castelán
  • Edwin R. Hancock
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)


In previous work [5] we have identified the gradient of the surface as the best representation for constructing Cartesian models of faces. This representation proved capable of capturing variations in facial shape over a sample of training data. The resulting statistical model can be fitted to Lambertian data using a simple non-exhaustive parameter adjustment procedure. In this paper we test the ability of the surface gradient-based model in two directions. First, we deal with non-lambertian images. Second, we use the model for face recognition purposes. Experiments with real world images suggest that the surface gradient model with the proposed parameter search can be used for accurate face shape recovery, showing a potential for face recognition applications.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Mario Castelán
    • 1
  • Edwin R. Hancock
    • 2
  1. 1.Centro de Investigación y Estudios Avanzados del I.P.N., Ramos Arizpe 25900, CoahuilaMexico
  2. 2.The University of York, Heslington, York YO10 5DDUnited Kingdom

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