bibtype J - Journal Article
ARLID 0501036
utime 20240111141015.1
mtime 20190205235959.9
SCOPUS 85061215223
WOS 000460393600001
DOI 10.1145/3301412
title (primary) (eng) Perceptual Attributes Analysis of Real-World Materials
specification
page_count 19 s.
media_type P
serial
ARLID cav_un_epca*0329828
ISSN 1544-3558
title ACM Transactions on Applied Perception
volume_id 16
publisher
name Association for Computing Machinery
keyword BRDF
keyword attributes
keyword perception
keyword visual
keyword tactile
keyword user study
author (primary)
ARLID cav_un_auth*0101086
full_dept Department of Pattern Recognition
share 80
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
garant K
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0361777
full_dept Department of Pattern Recognition
share 20
name1 Kolafová
name2 Martina
institution UTIA-B
full_dept (cz) Rozpoznávání obrazu
full_dept Department of Pattern Recognition
department (cz) RO
department RO
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
source_type PDF
url http://library.utia.cas.cz/separaty/2019/RO/filip-0501036.pdf
source_size 15MB
source
url https://dl.acm.org/doi/10.1145/3301412
cas_special
project
ARLID cav_un_auth*0347019
project_id GA17-18407S
agency GA ČR
abstract (eng) Material appearance is often represented by a bidirectional reflectance distribution function (BRDF). Although the concept of the BRDF is widely used in computer graphics and related applications, the number of actual captured BRDFs is limited due to a time and resources demanding measurement process. Several BRDF databases have already been provided publicly, yet subjective properties of underlying captured material samples, apart from single photographs, remain unavailable for users. In this paper we analyzed material samples, used in the creation of the UTIA BRDF database, in a psychophysical study with nine subjects and assessed its twelve visual, tactile, and subjective attributes. Further, we evaluated the relationship between the attributes and six material categories. We consider the presented perceptual analysis as valuable and complementary information to the database, that could aid users to select appropriate materials for their applications.
result_subspec WOS
RIV BD
FORD0 20000
FORD1 20200
FORD2 20205
reportyear 2020
num_of_auth 2
mrcbC52 4 A hod 4ah 20231122143808.3
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0293335
mrcbC61 1
mrcbC64 1 Department of Pattern Recognition UTIA-B 10201 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
confidential S
article_num 1
mrcbC86 3+4 Article Computer Science Software Engineering
mrcbC91 C
mrcbT16-e COMPUTERSCIENCESOFTWAREENGINEERING
mrcbT16-j 0.409
mrcbT16-s 0.489
mrcbT16-B 48.642
mrcbT16-D Q3
mrcbT16-E Q3
arlyear 2019
mrcbTft \nSoubory v repozitáři: filip-0501036.pdf
mrcbU14 85061215223 SCOPUS
mrcbU24 PUBMED
mrcbU34 000460393600001 WOS
mrcbU56 PDF 15MB
mrcbU63 cav_un_epca*0329828 ACM Transactions on Applied Perception 1544-3558 1544-3965 Roč. 16 č. 1 2019 Association for Computing Machinery