0486111 20240111140956.520180205235959.9 85044303328 10.1145/3154353.3154370 9 s. E cav_un_epca*0486110978-1-4503-5107-2New YorkACM2017SpencerStephen N. BRDF gloss material specular goniometer adaptive measurement chrome-like appearance high-reflective mirror-like coatings cav_un_auth*0101086 Department of Pattern Recognition 45 Filip Jiří UTIA-B Rozpoznávání obrazu Department of Pattern Recognition RO RO K Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0282273 Department of Pattern Recognition 45 Vávra Radomír UTIA-B Rozpoznávání obrazu Department of Pattern Recognition RO RO Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0330886 10 Maile F. J. DE PDF http://library.utia.cas.cz/separaty/2017/RO/filip-0486111.pdf 11MB cav_un_auth*0347019 GA17-18407S GA ČR Visually accurate capture of appearance of highly specular surfaces is of a great research interest of the coating industry, who strive to introduce highly reflective products while minimizing their production and quality assessment costs, and avoiding environmental issues related to the production process. An efficient measurement of such surfaces is challenging due to their narrow specular peak of an unknown shape and typically very high dynamic range. Such behavior puts higher requirements on capabilities of a measuring device and has impact on length of the measurement process. In this paper, we rely on a material probes with a predefined curved shape featuring slight local inhomogeneities. This defines a goniometric device as appropriate means of appearance capture. To shorten a typically long measurement time required when using these approaches, we introduce a method of material appearance acquisition by means of the isotropic BRDF using relatively sparse sampling adapted to each measured material individually. cav_un_auth*0357891 SCCG´17 - 33rd Spring Conference on Computer Graphics 2017 20170515 20170517 Mikulov CZ BD 10000 10200 10201 2018 3 PR RVO:67985556 http://hdl.handle.net/11104/0281412 1 cav_un_auth*0357892 Schlenk Metallic Pigments GmbH SCHLENK DE S 13 2017 85044303328 SCOPUS PUBMED WOS PDF 11MB cav_un_epca*0486110 Proceedings of the 33rd Spring Conference on Computer Graphics 978-1-4503-5107-2 13:1-13:9 New York ACM 2017 SCCG '17 340 Spencer Stephen N.