CuRRET: Columbia-Utrecht Reflectance and Texture Database. 3 databases: 1) BRDF (bidirectional reflectance distribution function) database with reflectance measurements for over 60 different samples, each observed with over 200 different combinations of viewing and illumination directions. 2) BRDF parameter database with fitting parameters from two recent BRDF models: the Oren-Nayar model and the Koenderink et al. representation. These BRDF parameters can be directly used for both image analysis and image synthesis. 3) BTF (bidirectional texture function) database with image textures from over 60 different samples, each observed with over 200 different combinations of viewing and illumination directions. Each of these databases is made publicly available for research purposes. For details about the measurements, and fitting procedures a technical report and summary paper are provided.

References in zbMATH (referenced in 48 articles )

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  1. Lindeberg, Tony: Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade (2020)
  2. Chi, Jianning; Yu, Xiaosheng; Zhang, Yifei; Wang, Huan: A novel local human visual perceptual texture description with key feature selection for texture classification (2019)
  3. Liu, Jinping; He, Jiezhou; Tang, Zhaohui; Xu, Pengfei; Zhang, Wuxia; Gui, Weihua: Characterization of complex image spatial structures based on symmetrical Weibull distribution model for texture pattern classification (2018)
  4. Cherian, Anoop; Sra, Suvrit: Positive definite matrices: data representation and applications to computer vision (2016)
  5. Guo, Yimo; Zhao, Guoying; Pietikäinen, Matti: Local configuration features and discriminative learnt features for texture description (2014) ioport
  6. Perea, Jose A.; Carlsson, Gunnar: A Klein-bottle-based dictionary for texture representation (2014)
  7. Bouguila, Nizar: On the smoothing of multinomial estimates using Liouville mixture models and applications (2013)
  8. Maani, Rouzbeh; Kalra, Sanjay; Yang, Yee-Hong: Noise robust rotation invariant features for texture classification (2013) ioport
  9. Sharan, Lavanya; Liu, Ce; Rosenholtz, Ruth; Adelson, Edward H.: Recognizing materials using perceptually inspired features (2013)
  10. Tunwattanapong, Borom; Fyffe, Graham; Graham, Paul; Busch, Jay; Yu, Xueming; Ghosh, Abhijeet; Debevec, Paul: Acquiring reflectance and shape from continuous spherical harmonic illumination (2013)
  11. Aptoula, Erchan: Extending morphological covariance (2012) ioport
  12. Guo, Yimo; Zhao, Guoying; Pietikäinen, Matti: Discriminative features for texture description (2012) ioport
  13. Haindl, Michal; Havlíček, Vojtěch; Grim, Jiří: Probabilistic mixture-based image modelling (2011)
  14. Ilea, Dana E.; Whelan, Paul F.: Image segmentation based on the integration of colour-texture descriptors -- a review (2011)
  15. Campana, Bilson J. L.; Keogh, Eamonn J.: A compression-based distance measure for texture (2010)
  16. Crosier, M.; Griffin, L. D.: Using basic image features for texture classification (2010) ioport
  17. Greiner, T.; Rao, Shivani G.; Das, Sukhendu: Estimation of orientation of a textured planar surface using projective equations and separable analysis with (M)-channel wavelet decomposition (2010)
  18. Guo, Zhenhua; Zhang, Lei; Zhang, David: Rotation invariant texture classification using LBP variance (LBPV) with global matching (2010)
  19. Smith, William A. P.; Hancock, Edwin R.: Estimating facial reflectance properties using shape-from-shading (2010) ioport
  20. Xia, Gui-Song; Delon, Julie; Gousseau, Yann: Shape-based invariant texture indexing (2010) ioport

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