Abstract
Visual scene recognition is predominantly based on visual textures representing an object’s material properties. However, the single material texture varies in scale and illumination angles due to mapping an object’s shape. We present an anisotropy criterion of bidirectional reflectance distribution function (BRDF), which allows deciding if a simpler isotropic BRDF model can be used or if it is necessary to use a more complex anisotropic BRDF model. The criterion simultaneously shows dominant angular orientations for the anisotropic materials. The anisotropic criterion is tested on several isotropic and anisotropic surface materials, with BRDF computed from the measured seven-dimensional Bidirectional Texture Function.
The Czech Science Foundation project GAČR 19-12340S supported this research.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
References
Ashikhmin, M., Shirley, P.: An anisotropic phong BRDF model. J. Graph. Tools 5(2), 25–32 (2000)
Bell, S., Upchurch, P., Snavely, N., Bala, K.: Material recognition in the wild with the materials in context database. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3479–3487 (2015)
Blinn, J.F.: Models of light reflection for computer synthesized pictures. In: Proceedings of the 4th Annual Conference on Computer Graphics and Interactive Techniques, pp. 192–198. ACM Press (1977)
Cook, R.L., Torrance, K.E.: A reflectance model for computer graphics. ACM Trans. Graph. (TOG) 1(1), 7–24 (1982)
Edwards, D., et al.: The halfway vector disk for BRDF modeling. ACM Trans. Graph. (TOG) 25(1), 1–18 (2006)
Gibert, X., Patel, V.M., Chellappa, R.: Material classification and semantic segmentation of railway track images with deep convolutional neural networks. In: 2015 IEEE International Conference on Image Processing (ICIP), pp. 621–625. IEEE (2015)
Haindl, M., Filip, J.: Visual Texture. Advances in Computer Vision and Pattern Recognition, Springer, London (2013). https://doi.org/10.1007/978-1-4471-4902-6, https://link.springer.com/book/10.1007/978-1-4471-4902-6
Haindl, M., Filip, J., Vávra, R.: Digital material appearance: the curse of tera-bytes. ERCIM News (90), 49–50 (2012). https://ercim-news.ercim.eu/en90/ri/digital-material-appearance-the-curse-of-tera-bytes
Haindl, M., Mikeš, S., Kudo, M.: Unsupervised surface reflectance field multi-segmenter. In: Azzopardi, G., Petkov, N. (eds.) CAIP 2015. LNCS, vol. 9256, pp. 261–273. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23192-1_22
Haindl, M., Vácha, P.: Wood veneer species recognition using Markovian textural features. In: Azzopardi, G., Petkov, N. (eds.) CAIP 2015. LNCS, vol. 9256, pp. 300–311. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23192-1_25
Hapke, B.W.: A theoretical photometric function for the lunar surface. J. Geophys. Res. 68(15), 4571–4586 (1963)
Lafortune, E., Foo, S., Torrance, K., Greenberg, D.: Non-linear approximation of reflectance functions. In: ACM SIGGRAPH 1997, pp. 117–126. ACM Press (1997)
Lewis, R.R.: Making shaders more physically plausible. In: Computer Graphics Forum, vol. 13, pp. 109–120. Wiley Online Library (1994)
Minnaert, M.: The reciprocity principle in lunar photometry. Astrophys. J. 93, 403–410 (1941)
Nayar, S.K., Oren, M.: Visual appearance of matte surfaces. Science 267(5201), 1153–1156 (1995)
Neumann, L., Neumannn, A., Szirmay-Kalos, L.: Compact metallic reflectance models. In: Computer Graphics Forum, vol. 18, pp. 161–172. Wiley Online Library (1999)
Oren, M., Nayar, S.K.: Generalization of lambert’s reflectance model. In: Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques, pp. 239–246 (1994)
Phong, B.T.: Illumination for computer generated pictures. Commun. ACM 18(6), 311–317 (1975)
Remeš, V., Haindl, M.: Bark recognition using novel rotationally invariant multispectral textural features. Pattern Recogn. Lett. 125, 612–617 (2019)
Schlick, C.: A customizable reflectance model for everyday rendering. In: Fourth Eurographics Workshop on Rendering, Paris, France, pp. 73–83 (1993)
Schlick, C.: An inexpensive BRDF model for physically-based rendering. In: Computer graphics forum, vol. 13, pp. 233–246. Wiley Online Library (1994)
Torrance, K.E., Sparrow, E.M.: Off-specular peaks in the directional distribution of reflected thermal radiation. J. Heat Transf. 6(7), 223–230 (1966)
Trowbridge, T., Reitz, K.P.: Average irregularity representation of a rough surface for ray reflection. JOSA 65(5), 531–536 (1975)
Varma, M., Zisserman, A.: A statistical approach to material classification using image patch exemplars. IEEE Trans. Pattern Anal. Mach. Intell. 31(11), 2032–2047 (2009). http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.182
Ward, G.: Measuring and modeling anisotropic reflection. Comput. Graph. 26(2), 265–272 (1992)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Haindl, M., Havlíček, V. (2022). BRDF Anisotropy Criterion. In: Nguyen, N.T., Tran, T.K., Tukayev, U., Hong, TP., Trawiński, B., Szczerbicki, E. (eds) Intelligent Information and Database Systems. ACIIDS 2022. Lecture Notes in Computer Science(), vol 13758. Springer, Cham. https://doi.org/10.1007/978-3-031-21967-2_35
Download citation
DOI: https://doi.org/10.1007/978-3-031-21967-2_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-21966-5
Online ISBN: 978-3-031-21967-2
eBook Packages: Computer ScienceComputer Science (R0)