Perceptual dimensions of wood materials

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F24%3A00586421" target="_blank" >RIV/67985556:_____/24:00586421 - isvavai.cz</a>

Alternative codes found

RIV/68081740:_____/24:00586421

Result on the web

<a href="https://jov.arvojournals.org/article.aspx?articleid=2793694" target="_blank" >https://jov.arvojournals.org/article.aspx?articleid=2793694</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1167/jov.24.5.12" target="_blank" >10.1167/jov.24.5.12</a>

Result language

angličtina

Original language name

Perceptual dimensions of wood materials

Original language description

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.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20201 - Electrical and electronic engineering

Project

<a href="/en/project/GA22-17529S" target="_blank" >GA22-17529S: Visual fingerprint of material appearance</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Vision

ISSN

1534-7362

e-ISSN

1534-7362

Volume of the periodical

24

Issue of the periodical within the volume

5

Country of publishing house

US - UNITED STATES

Number of pages

21

Pages from-to

12

UT code for WoS article

001281930500012

EID of the result in the Scopus database

2-s2.0-85194126723