Image-based appearance acquisition of effect coatings
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00504286" target="_blank" >RIV/67985556:_____/19:00504286 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s41095-019-0134-3" target="_blank" >https://link.springer.com/article/10.1007/s41095-019-0134-3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s41095-019-0134-3" target="_blank" >10.1007/s41095-019-0134-3</a>
Alternative languages
Result language
angličtina
Original language name
Image-based appearance acquisition of effect coatings
Original language description
Paint manufacturers strive to introduce unique visual effects to coatings in order to visually communicate functional properties of products using value-added, customized design. However, these effects often feature complex angularly dependent spatially-varying behavior, thus representing a challenge in digital reproduction. In this paper we analyze several approaches to capturing spatially-varying appearance of effect coatings. We compare a baseline approach based on bidirectional texture function (BTF) with four variants of half-difference parameterization. Through a psychophysical study we identify minimal sampling along individual dimensions of this parametrization. We conclude that bivariate representations preserve visual fidelity of effect coatings, while in contrast to BTF, better characterizing near-specular behavior and significantly restricting number of captured images.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/GA17-18407S" target="_blank" >GA17-18407S: Perceptually Optimized Measurement of Material Appearance</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computational Visual Media
ISSN
2096-0433
e-ISSN
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Volume of the periodical
5
Issue of the periodical within the volume
1
Country of publishing house
CN - CHINA
Number of pages
17
Pages from-to
73-89
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85064275364