Bidirectional Texture Function Simultaneous Autoregressive Model

Abstract. The Bidirectional Texture Function (BTF) is the recent most advanced representation of visual properties of surface materials. It specifies their altering appearance due to varying illumination and viewing conditions. Corresponding huge BTF measurements require a mathematical representation allowing simultaneously extremal compression as well as high visual fidelity. We present a novel Markovian BTF model based on a set of underlying simultaneous autoregressive models (SAR). This complex but efficient BTF-SAR model combines several multispectral band limited spatial factors and range map sub-models to produce the required BTF texture space. The BTF-SAR model enables very high BTF space compression ratio, texture enlargement, and reconstruction of missing unmeasured parts of the BTF space.

We have tested the BTF-SAR model algorithm on BTF colour textures from the University of Bonn BTF measurements (several available materials such
as leather, wood, wool). Each BTF material sample comprised in the University of Bonn database is measured in 81 illumination and 81 viewing angles and
has resolution 800 × 800 pixels, so that 81 × 81 images had to be analysed for each material. Following figures demonstrate the synthesised result for two different wood samples, i.e. synthesised BTF textures combined with their range maps in the displacement mapping filter of the rendering software (Blender) with the BTF pluggin and mapped to the detailed conch model measured using our Konika-Minolta laser scanner.

Haindl, M., and M. Havlíček, "Bidirectional Texture Function Simultaneous Autoregressive Model", MUSCLE, (Pisa, IT, 13.12.2011-15.12.2011), vol. 7252, Pisa, Springer Berlin Heidelberg, pp. 149-159, 2012.
Havlíček, M., "MSAR BTF Model", Doktorandské dny 2011, 1, vol. 1, issue 1, Praha, České vysoké učení technické v Praze, pp. 47-56, 11/2011.