bibtype J - Journal Article
ARLID 0586421
utime 20250310160013.2
mtime 20240604235959.9
SCOPUS 85194126723
WOS 001281930500012
DOI 10.1167/jov.24.5.12
title (primary) (eng) Perceptual dimensions of wood materials
specification
page_count 21 s.
media_type E
serial
ARLID cav_un_epca*0040199
ISSN 1534-7362
title Journal of Vision
volume_id 24
publisher
name Association for Research in Vision and Ophthalmology
keyword texture
keyword surface
keyword categorization
keyword dimension
keyword color
keyword similarity
keyword wood
keyword material
keyword perception
keyword rating
author (primary)
ARLID cav_un_auth*0101086
name1 Filip
name2 Jiří
institution UTIA-B
full_dept (cz) Rozpoznávání obrazu
full_dept (eng) Department of Pattern Recognition
department (cz) RO
department (eng) RO
full_dept Department of Pattern Recognition
garant K
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0106408
name1 Lukavský
name2 Jiří
institution PSU-E
full_dept (cz) Kognitivní psychologie
full_dept Department of Cognitive Psychology
full_dept Institute of psychology
country CZ
fullinstit Psychologický ústav AV ČR, v. v. i.
author
ARLID cav_un_auth*0294719
name1 Děchtěrenko
name2 Filip
institution PSU-E
full_dept (cz) Kognitivní psychologie
full_dept Department of Cognitive Psychology
full_dept Institute of psychology
country CZ
fullinstit Psychologický ústav AV ČR, v. v. i.
author
ARLID cav_un_auth*0340873
name1 Schmidt
name2 F.
country DE
author
ARLID cav_un_auth*0468180
name1 Fleming
name2 R. W.
country DE
source
url https://library.utia.cas.cz/separaty/2024/RO/filip-0586421.pdf
source
url https://jov.arvojournals.org/article.aspx?articleid=2793694
cas_special
project
project_id GA22-17529S
agency GA ČR
country CZ
ARLID cav_un_auth*0439849
abstract (eng) 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.
result_subspec WOS
RIV BD
FORD0 20000
FORD1 20200
FORD2 20201
reportyear 2025
mrcbC47 PSU-E 50000 50100 50101
mrcbC52 4 A sml 4as 2rh 20240624073912.4 2 R hod 20250310154715.8 20250310160013.2
inst_support RVO:67985556
inst_support RVO:68081740
permalink https://hdl.handle.net/11104/0353953
confidential S
contract
name LICENSE TO PUBLISH
date 20230417
article_num 12
mrcbC91 A
mrcbT16-e OPHTHALMOLOGY
mrcbT16-j 0.719
mrcbT16-s 0.849
mrcbT16-D Q2
mrcbT16-E Q2
arlyear 2024
mrcbTft \nSoubory v repozitáři: filip-0586421.pdf, filip-0586421-copyright.pdf
mrcbU14 85194126723 SCOPUS
mrcbU24 38787569 PUBMED
mrcbU34 001281930500012 WOS
mrcbU63 cav_un_epca*0040199 Journal of Vision 1534-7362 1534-7362 Roč. 24 č. 5 2024 Association for Research in Vision and Ophthalmology