Material fingerprinting: predicting human perception of material appearance through psychophysical analysis and neural networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00641338" target="_blank" >RIV/67985556:_____/25:00641338 - isvavai.cz</a>

Alternative codes found

RIV/68081740:_____/25:00641338

Result on the web

<a href="https://royalsocietypublishing.org/rsos/article/12/11/250513/234224/Material-fingerprinting-predicting-human" target="_blank" >https://royalsocietypublishing.org/rsos/article/12/11/250513/234224/Material-fingerprinting-predicting-human</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1098/rsos.250513" target="_blank" >10.1098/rsos.250513</a>

Result language

angličtina

Original language name

Material fingerprinting: predicting human perception of material appearance through psychophysical analysis and neural networks

Original language description

Digital representation of materials is crucial in fields such as virtual reality, industrial design and quality control. However, predicting human perception of materials from image data is challenging due to the complexity of material appearances and the intricacies of human vision. This study introduces a perceptual representation termed the ‘visual fingerprint’, linking image-based measurements of materials to intuitive, human-understandable attributes. We conducted psychophysical studies using standardized video sequences of 347 diverse real-world materials, including fabrics and wood, selected to encompass a broad spectrum of textures, colours and reflective properties. Sixteen key appearance attributes were identified, and over 110 000 human ratings were collected to map perceptual attributes across material categories. By integrating CLIP-derived image features with a multi-layer perceptron model, we developed a predictive framework for material perception. Our results demonstrate that human judgements of appearance and similarity can be accurately predicted using only two images of a material. This work offers a practical and interpretable approach to material representation, enabling intuitive comparisons and retrievals in applications where material appearance is crucial. The proposed material fingerprint and its prediction directly from image data represent a significant step towards simplifying the understanding and interoperability of material properties in diverse digital environments.

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

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

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

2025

Confidentiality

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

Name of the periodical

Royal Society Open Science

ISSN

2054-5703

e-ISSN

2054-5703

Volume of the periodical

12

Issue of the periodical within the volume

11

Country of publishing house

GB - UNITED KINGDOM

Number of pages

21

Pages from-to

250513

UT code for WoS article

001618124500012

EID of the result in the Scopus database

2-s2.0-105021299046