Highly-realistic materials in computer graphics are computationally and memory demanding. Currently, the most versatile techniques are based on Bidirectional Texture Functions (BTFs), an image-based approximation of appearance. Extremely realistic images may be quickly obtained with BTFs at the price of a huge amount of data. Even though a lot of BTF compression schemes have been introduced during the last years, the main remaining challenge arises from the fact that a BTF embeds many different optical phenomena generated by the underlying meso-geometry (parallax effects, masking, shadow casting, inter-reflections, etc.). We introduce a new representation for BTFs that isolates parallax effects. On one hand, we built a flattened BTF according to a global spatial parameterization of the underlying meso-geometry. On the other hand, we generate a set of view-dependent indirection maps on this spatial parameterization to encode all the parallax effects. We further analyze this representation on a various set of synthetic BTF data to show its benefits on view-dependent coherency, and to find the best sampling strategy. We also demonstrate that this representation is well suited for hardware acceleration on current GPUs.
