Recent progress in the measurement of surface reflectance has created
a demand for non-parametric appearance representations that
are accurate, compact, and easy to use for rendering. Another crucial
goal, which has so far received little attention, is editability: for
practical use, we must be able to change both the directional and
spatial behavior of surface reflectance (e.g., making one material
shinier, another more anisotropic, and changing the spatial "texture
maps" indicating where each material appears). We introduce an
Inverse Shade Tree framework that provides a general approach to
estimating the "leaves" of a user-specified shade tree from high-dimensional
measured datasets of appearance. These leaves are
sampled 1- and 2-dimensional functions that capture both the directional
behavior of individual materials and their spatial mixing
patterns. In order to compute these shade trees automatically, we
map the problem to matrix factorization and introduce a flexible
new algorithm that allows for constraints such as non-negativity,
sparsity, and energy conservation. Although we cannot infer every
type of shade tree, we demonstrate the ability to reduce multigigabyte
measured datasets of the Spatially-Varying Bidirectional
Reflectance Distribution Function (SVBRDF) into a compact representation
that may be edited in real time.
Jason Lawrence, Aner Ben-Artzi, Christopher DeCoro, Wojciech Matusik, Hanspeter Pfister, Ravi Ramamoorthi, and Szymon Rusinkiewicz.
"Inverse Shade Trees for Non-Parametric Material Representation and Editing."
ACM Transactions on Graphics (Proc. SIGGRAPH) 25(3), July 2006.
author = "Jason Lawrence and Aner Ben-Artzi and Christopher DeCoro and Wojciech
Matusik and Hanspeter Pfister and Ravi Ramamoorthi and Szymon
title = "Inverse Shade Trees for Non-Parametric Material Representation and
journal = "ACM Transactions on Graphics (Proc. SIGGRAPH)",
year = "2006",
month = jul,
volume = "25",
number = "3"