|Data-Driven Diffuse-Specular Separation from Spherical Gradient Illumination|
|SIGGRAPH 2009 Poster|
|Tongbo Chen Abhijeet Ghosh Paul Debevec|
|USC Institute for Creative Technologies|
Recently, Ma et al.  introduced a technique for estimating high quality diffuse and specular normals and albedo maps using polarized spherical gradient illumination. However, the polarization based technique restricts acquisition to a single viewpoint, needs observation of two polarization states and results in insufficient light levels for performance capture. In this work, we look into an alternate diffuse-specular separation technique for spherical gradients based on a data-driven reflectance model.
Our separation algorithm proceeds in two stages.
First, we employ example data with known ground
truth separation to build orientation-based
reflectance profiles for diffuse and specular
reflectance under the uniform spherical illumination
condition. Thereafter, we employ the diffuse and
specular reflectance profiles to split the uniform
illumination observation into diffuse and specular
albedos (Figure 1, (b)). The above separation serves as
an initial guess for the following iterative
optimization: we relight the separated diffuse and
specular albedo into the X, Y and Z gradient
illuminations, sum them up and then compare to
the observed unseparated gradients. The error in the
relit conditions is attributed alternately to the
specular normal estimate and to the specular albedo
estimate in subsequent iterations. We repeat the
above normal and albedo updates for a few
iterations until convergence.
In this work, we consider the polarization based separation of Ma et al. to be the ground-truth diffuse-specular separation of albedo and surface normals. We employ our example-based data-driven separation on the parallel-polarized images (Figure 1, (c) & (e)) in order to compare the proposed separation technique with the polarization-based results. Figure 2 shows separation results for a human face in a static neutral expression as well as two dynamic performance capture settings.
- (paper) Data-DrivenSeparation_SiggraphPoster09.pdf, 4.22 MB.
- (poster) Data-DrivenSeparation_4ftx3ft_Poster.png, 6.30 MB.
- Light Stage 5:
- Surface Reflectometry: