0431132 20240111140850.120140912235959.9 84919933899 000359818002028 10.1109/ICPR.2014.357 6 s. C cav_un_epca*0431131978-1-4799-5208-31051-46512047-2052StockholmIEEE Computer Society2014 BRDF measurement anisotropic goniometer cav_un_auth*0101086 50 Filip Jiří UTIA-B Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0282273 40 Vávra Radomír UTIA-B Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0283206 10 Havlíček Michal UTIA-B Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. hypertextový soubor PDF http://library.utia.cas.cz/separaty/2014/RO/filip-0431132.pdf 3MB cav_un_auth*0303439 GA14-10911S GA ČR CZ cav_un_auth*0303412 GA14-02652S GA ČR CZ cav_un_auth*0273627 GAP103/11/0335 GA ČR 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. cav_un_auth*0305624 ICPR 2014 - The 22nd International Conference on Pattern Recognition 24.08.2014-28.08.2014 Stockholm SE BD 10000 10200 10201 2015 PO RVO:67985556 http://hdl.handle.net/11104/0236069 S RIV/67985556:_____/14:00431132!RIV15-AV0-67985556 152459699 Doplnění UT WOS a Scopus RIV/67985556:_____/14:00431132!RIV15-GA0-67985556 152500651 Doplnění UT WOS a Scopus n.a. Proceedings Paper Computer Science Artificial Intelligence|Computer Science Theory Methods|Engineering Electrical Electronic 50 0.293 11.42 0.77 Q3 2014 84919933899 SCOPUS 000359818002028 WOS hypertextový soubor PDF 3MB cav_un_epca*0431131 Proceedings of the 22nd International Conference on Pattern Recognition (ICPR 2014) 978-1-4799-5208-3 1051-4651 2047 2052 Stockholm IEEE Computer Society 2014