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Reflectance of Human Faces: Image-Based Measurement and Modeling

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons44457

Fuchs,  Martin
Computer Graphics, MPI for Informatics, Max Planck Society;
Computer Graphics, MPI for Informatics, Max Planck Society;

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Citation

Fuchs, M. (2004). Reflectance of Human Faces: Image-Based Measurement and Modeling. Diploma Thesis, Universität des Saarlandes, Saarbrücken.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-2B1E-5
Abstract
An image-based acquisition pipeline for the reflective properties of a human face is presented, proposing an approach which extracts geometry and a spatially varying BRDF of a human face from few measurements in calibrated point light conditions. Applying the morphable face model introduced by Blanz-Vetter for the estimation of geometry in each of the input images, we gain an image-based geometry estimation which does not require range scans of the individual face, and obtain a parameterization of the face surface, which is consistent for all human faces. By means of non-linear optimization, we recover spatially varying parameters for an analytic BRDF model; the resulting BRDF function, together with the estimated geometry, creates a relightable representation of the face. The set of images used for the reflectance measurement is identical to the set of images used for the geometry estimation. Several BRDF models (Cook-Torrance, Lafortune, Ward, and a custom phe\-nom\-e\-no\-logical model) are compared in an experiment.