Bidirectional texture function
Bidirectional texture function (BTF) 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 and similar terms have since been introduced including BSSRDF 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. Application of the BTF is in photorealistic material rendering of objects in virtual reality systems and for visual scene analysis, 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.
Bidirectional texture function (BTF) [1][2][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 [1][2] and similar terms have since been introduced including BSSRDF[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.[3][5]
Application of the BTF is in photorealistic material rendering of objects in virtual reality systems and for visual scene analysis,[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.[7]
See also
[edit]- 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
References
[edit]- ^ a b Kristin 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.
- ^ a b Kristin 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) - ^ a b Jiří 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.
- ^ Jensen, 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) - ^ Vlastimil 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.
- ^ Michal 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.
- ^ Oana G. Cula; Kristin J. Dana; Frank P. Murphy; Babar K. Rao (2005). "Skin Texture Modeling". International Journal of Computer Vision: 97–119.