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Bidirectional texture function (BTF) cite-ref-r3-1-0[1]cite-ref-r4-2-0[2]cite-ref-r1-3-0[3] is a 6-dimensional function depending on planar texture coordinates (x,y) as well as on view and illumination spherical angles. In practice this function is obtained as a set of several thousand color images of material sample taken during different camera and light positions.

The BTF is a representation of the appearance of texture as a function of viewing and illumination direction. It is an image-based representation, since the geometry of the surface is unknown and not measured. BTF is typically captured by imaging the surface at a sampling of the hemisphere of possible viewing and illumination directions. BTF measurements are collections of images. The term BTF was first introduced in cite-ref-r3-1-1[1]cite-ref-r4-2-1[2] and similar terms have since been introduced including BSSRDFcite-ref-r5-4-0[4] and SBRDF (spatial BRDF). SBRDF has a very similar definition to BTF, i.e. BTF is also a spatially varying BRDF.

To cope with a massive BTF data with high redundancy, many compression methods were proposed.cite-ref-r1-3-1[3]cite-ref-r2-5-0[5]

Application of the BTF is in photorealistic material rendering of objects in virtual reality systems and for visual scene analysis,cite-ref-r7-6-0[6] e.g., recognition of complex real-world materials using bidirectional feature histograms or 3D textons.

Biomedical and biometric applications of the BTF include recognition of skin texture.cite-ref-r6-7-0[7]

• See also

• References

• BSDF == BRDF + BTDF, a 4+1 dimensional function of the scattering distribution from a single point/pixel/vertex.

• Columbia Utrecht Reflectance and Texture Database

• BTF Database Bonn and Measurement Lab

• CVPR 2010 BTF Modeling Tutorial

• BTFbase - BTF compression based on a multi-level vector quantization (free BTF shader)

• UTIA BTF Database - a new source of publicly available bidirectional texture function measurements

cite-note-r3-11. ↑ citerefkristin-j-danabram-van-ginnekenshree-k-nayarjan-j-koenderink1999Kristin J. Dana; Bram van Ginneken; Shree K. Nayar; Jan J. Koenderink (1999). "Reflectance and texture of real world surfaces". ACM Transactions on Graphics. 18 (1): 1–34. doi:10.1145/300776.300778. S2CID 622815.

cite-note-r4-22. ↑ citerefkristin-j-danabram-van-ginnekenshree-k-nayarjan-j-koenderink1996Kristin J. Dana; Bram van Ginneken; Shree K. Nayar; Jan J. Koenderink (1996). "Reflectance and texture of real world surfaces". Columbia University Technical Report CUCS-048-96. {{cite web}}: Missing or empty |url= (help)

cite-note-r1-33. ↑ citerefji-filipmichal-haindl2009Jiří Filip; Michal Haindl (2009). "Bidirectional Texture Function Modeling: A State of the Art Survey". IEEE Transactions on Pattern Analysis and Machine Intelligence. 31 (11): 1921–1940. CiteSeerX 10.1.1.494.2660. doi:10.1109/TPAMI.2008.246. PMID 19762922. S2CID 9283615.

cite-note-r5-44. ↑ citerefjensen-h-w-marschner-s-r-levoy-m-hanrahan-p-2001Jensen, H.W.; Marschner, S.R.; Levoy, M.; Hanrahan, P. (2001). "A practical model for subsurface light transport". ACM SIGGRAPH. pp. 511–518. {{cite web}}: Missing or empty |url= (help)

cite-note-r2-55. ↑ citerefvlastimil-havranji-filipkarol-myszkowski2009Vlastimil Havran; Jiří Filip; Karol Myszkowski (2009). "Bidirectional Texture Function Compression based on Multi-Level Vector Quantization". Computer Graphics Forum. 29 (1): 175–190. Archived from the original on 2010-08-04.

cite-note-r7-66. ↑ citerefmichal-haindlji-filip2013Michal Haindl; Jiří Filip (2013). Visual Texture: Accurate Material Appearance Measurement, Representation and Modeling. Advances in Computer Vision and Pattern Recognition. Springer-Verlag London 2013. p. 285. ISBN 978-1-4471-4901-9.

cite-note-r6-77. ↑ citerefoana-g-culakristin-j-danafrank-p-murphybabar-k-rao2005Oana G. Cula; Kristin J. Dana; Frank P. Murphy; Babar K. Rao (2005). "Skin Texture Modeling". International Journal of Computer Vision: 97–119.