Inverse Shade Trees for Non-Parametric Material Representation and Editing


J. Lawrence; A. Ben-Artzi; C. DeCoro; W. Matusik; H. Pfister; R. Ramamiirthi; S. Ruskinkiewicz


Recent progress in the measurement of surface reectance 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 reectance (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-specied shade tree from highdimensional 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 exible 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 Reectance Distribution Function (SVBRDF) into a compact representation that may be edited in real time.

BibTex entry

@conference { 31, title = {Inverse Shade Trees for Non-Parametric Material Representation and Editing}, year = {2006}, month = {07/2006}, pages = {735-745}, author = {J. Lawrence and A. Ben-Artzi and C. DeCoro and W. Matusik and H. Pfister and R. Ramamiirthi and S. Ruskinkiewicz} }