0586421 20250310160013.220240604235959.9 85194126723 001281930500012 10.1167/jov.24.5.12 21 s. E cav_un_epca*00401991534-736224Association for Research in Vision and Ophthalmology texture surface categorization dimension color similarity wood material perception rating cav_un_auth*0101086 Filip Jiří UTIA-B Rozpoznávání obrazu Department of Pattern Recognition RO RO Department of Pattern Recognition K Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0106408 Lukavský Jiří PSU-E Kognitivní psychologie Department of Cognitive Psychology Institute of psychology CZ Psychologický ústav AV ČR, v. v. i. cav_un_auth*0294719 Děchtěrenko Filip PSU-E Kognitivní psychologie Department of Cognitive Psychology Institute of psychology CZ Psychologický ústav AV ČR, v. v. i. cav_un_auth*0340873 Schmidt F. DE cav_un_auth*0468180 Fleming R. W. DE https://library.utia.cas.cz/separaty/2024/RO/filip-0586421.pdf https://jov.arvojournals.org/article.aspx?articleid=2793694 GA22-17529S GA ČR CZ cav_un_auth*0439849 Materials exhibit an extraordinary range of visual appearances. Characterizing and quantifying appearance is important not only for basic research on perceptual mechanisms but also for computer graphics and a wide range of industrial applications. Although methods exist for capturing and representing the optical properties of materials and how they vary across surfaces (Haindl & Filip, 2013), the representations are typically very high-dimensional, and how these representations relate to subjective perceptual impressions of material appearance remains poorly understood. Here, we used a data-driven approach to characterizing the perceived appearance characteristics of 30 samples of wood veneer using a „visual fingerprint“ that describes each sample as a multidimensional feature vector, with each dimension capturing a different aspect of the appearance. Fifty-six crowd-sourced participants viewed triplets of movies depicting different wood samples as the sample rotated. Their task was to report which of the two match samples was subjectively most similar to the test sample. In another online experiment, 45 participants rated 10 wood-related appearance characteristics for each of the samples. The results reveal a consistent embedding of the samples across both experiments and a set of nine perceptual dimensions capturing aspects including the roughness, directionality, and spatial scale of the surface patterns. We also showed that a weighted linear combination of 11 image statistics, inspired by the rating characteristics, predicts perceptual dimensions well. WOS BD 20000 20200 20201 2025 PSU-E 50000 50100 50101 4 A sml 4as 2rh 20240624073912.4 2 R hod 20250310154715.8 20250310160013.2 RVO:67985556 RVO:68081740 https://hdl.handle.net/11104/0353953 S LICENSE TO PUBLISH 20230417 12 A OPHTHALMOLOGY 2.2 0.3 10.8 0.00623 0.803 9251 138 0.917 51.75 2.06 1157 Q1 2.000 132 Q2 69.2 0.99 Q2 69.2 2024 Soubory v repozitáři: filip-0586421.pdf, filip-0586421-copyright.pdf 85194126723 SCOPUS 38787569 PUBMED 001281930500012 WOS cav_un_epca*0040199 Journal of Vision 1534-7362 1534-7362 Roč. 24 č. 5 2024 Association for Research in Vision and Ophthalmology