We propose a new technique for efficiently rendering bidirectional texture functions (BTFs). A 6D BTF describesthe appearance of a material as a texture that depends on the lighting and viewing directions. As such, a BTFaccommodates self‐shadowing, interreflection, and masking effects of a complex material without needing anexplicit representation of the small scale geometry. Our method represents the BTF as a set of spatially varyingapparent BRDFs, that each encode the reflectance field of a single pixel in the BTF. Each apparent BRDF isdecomposed into a product of three or more two‐dimensional positive factors using a novel factorization technique,which we call chained matrix factorization (CMF). The proposed factorization technique is fully automatic andsuitable for both BRDFs and apparent BRDFs (which typically exhibit off‐specular peaks and non‐reciprocity).The main benefit of CMF is that it delivers factors well suited for the limited dynamic range of conventionaltexture maps. After factorization, an efficient representation of the BTF is obtained by clustering the factors intoa compact set of 2D textures. With this compact representation, BTFs can be rendered on recent consumer levelhardware with arbitrary viewing and lighting directions at interactive rates. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three‐DimensionalGraphics and Realism

Figure 1: A factored composite wax material model applied to the Stanford dragon. The material is composed of two kinds of wax with different scattering properties. Left: illuminated by an area light source from above. Middle: the material's diffuse albedo (no subsurface scattering). Right: illuminated from above by a texture projection light. AbstractMany translucent materials exhibit heterogeneous subsurface scattering, which arises from complex internal structures. The acquisition and representation of these scattering functions is a complex problem that has been only partially addressed in previous techniques. Unlike homogeneous materials, the spatial component of heterogeneous subsurface scattering can vary arbitrarily over surface locations. Storing the spatial component without compression leads to impractically large datasets. In this paper, we address the problem of acquiring and compactly representing the spatial component of heterogeneous subsurface scattering functions. We propose a material model based on matrix factorization that can be mapped onto arbitrary geometry, and, due to its compact form, can be incorporated into most visualization systems with little overhead. We present results of several real-world datasets that are acquired using a projector and a digital camera.

Figure 1: A factored composite wax material model applied to the Stanford dragon. The material is composed of two kinds of wax with different scattering properties. Left: illuminated by an area light source from above. Middle: the material's diffuse albedo (no subsurface scattering). Right: illuminated from above by a texture projection light. AbstractMany translucent materials exhibit heterogeneous subsurface scattering, which arises from complex internal structures. The acquisition and representation of these scattering functions is a complex problem that has been only partially addressed in previous techniques. Unlike homogeneous materials, the spatial component of heterogeneous subsurface scattering can vary arbitrarily over surface locations. Storing the spatial component without compression leads to impractically large datasets. In this paper, we address the problem of acquiring and compactly representing the spatial component of heterogeneous subsurface scattering functions. We propose a material model based on matrix factorization that can be mapped onto arbitrary geometry, and, due to its compact form, can be incorporated into most visualization systems with little overhead. We present results of several real-world datasets that are acquired using a projector and a digital camera.

A hyperspectral virtual forest scene of a Fagus sylvatica stand is presented. An off-the-shelf tree architectural software package (Bionatics) was used to generate a biologically accurate Fagus tree, while leaf BRDF data were acquired with the use of a hyperspectral Compact Laboratory Spectro-Goniometer (CLabSpeG). The goal behind the virtual forest scene is to create a Virtual Imaging System using measured BRDF data of vegetative material in order to improve existing canopy reflectance models. This imaging system is the first step towards the creation of a hyperspectral virtual laboratory that will be used to research and better understand earth solar interaction principles.

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