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Description
  • The development of novel analytical BRDF models, as well as adaptive BRDF sampling approaches, rely on the appropriate BRDF measurement of real materials. The quality of measurements is even more critical when it comes to accurately representing anisotropic materials where the character of anisotropy is unknown (locations of anisotropic highlights, their width, shape, etc.). As currently there is a lack of dense yet noise-free BRDF anisotropic datasets, we introduce such unique measurements of three anisotropic fabric materials. In this paper we discuss a method of dense BRDF data acquisition, post-processing, missing values interpolation, and analyze properties of the datasets. Our results are compared with photographs, dense data fitted and generated by two state-of-the art anisotropic BRDF models, and alternative measurements available.
  • The development of novel analytical BRDF models, as well as adaptive BRDF sampling approaches, rely on the appropriate BRDF measurement of real materials. The quality of measurements is even more critical when it comes to accurately representing anisotropic materials where the character of anisotropy is unknown (locations of anisotropic highlights, their width, shape, etc.). As currently there is a lack of dense yet noise-free BRDF anisotropic datasets, we introduce such unique measurements of three anisotropic fabric materials. In this paper we discuss a method of dense BRDF data acquisition, post-processing, missing values interpolation, and analyze properties of the datasets. Our results are compared with photographs, dense data fitted and generated by two state-of-the art anisotropic BRDF models, and alternative measurements available. (en)
Title
  • Effective Acquisition of Dense Anisotropic BRDF
  • Effective Acquisition of Dense Anisotropic BRDF (en)
skos:prefLabel
  • Effective Acquisition of Dense Anisotropic BRDF
  • Effective Acquisition of Dense Anisotropic BRDF (en)
skos:notation
  • RIV/68407700:21240/14:00221423!RIV15-MSM-21240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • I, P(GA14-02652S), P(GA14-10911S), P(GAP103/11/0335)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
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  • 13618
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21240/14:00221423
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • BRDF; measurement; goniometer (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [1348B2F87D5B]
http://linked.open...v/mistoKonaniAkce
  • Stockholm
http://linked.open...i/riv/mistoVydani
  • Los Alamitos
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 22nd International Conference on Pattern Recognition
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Filip, J.
  • Havlíček, M.
  • Vávra, Radomír
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1051-4651
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/ICPR.2014.357
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society
https://schema.org/isbn
  • 978-1-4799-5208-3
http://localhost/t...ganizacniJednotka
  • 21240
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