Using Cartesian Models of Faces with a Data-Driven and Integrable Fitting Framework

• Published in: Image Analysis and Recognition pp. 134 - 145
• Main Authors: Castelán, Mario, Hancock, Edwin R.
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2006
• Series: Lecture Notes in Computer Science
• Subjects: Azimuth Angle; Fourier Basis; Fourier Domain; Hard Constraint; Surface Gradient
• ISBN: 3540448942; 9783540448945
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11867661_13

We present an experimental analysis of four different ways of constructing three-dimensional statistical models of faces using Cartesian coordinates, namely: height, surface gradient, azimuthal angle and one based on Fourier domain basis functions. We test the ability of each of the models for dealing with information provided by shape-from-shading. Experiments show that representations based on directional information are more robust to noise than representations based on height information. Moreover, the method can be operated using a simple non-exhaustive parameter adjustment procedure and ensures that the recovered surface satisfies the image irradiance equation as a hard constraint subject to integrability conditions.