A similarity measure for material appearance

Lagunas, Manuel (Universidad de Zaragoza) ; Malpica, Sandra (Universidad de Zaragoza) ; Serrano, Ana (Universidad de Zaragoza) ; Garces, Elena ; Gutierrez, Diego (Universidad de Zaragoza) ; Masia, Belen (Universidad de Zaragoza)

Resumen: We present a model to measure the similarity in appearance between di erent materials, which correlates with human similarity judgments. We rst create a database of 9,000 rendered images depicting objects with varying materials, shape and illumination. We then gather data on perceived similarity from crowdsourced experiments; our analysis of over 114,840 answers suggests that indeed a shared perception of appearance similarity exists. We feed this data to a deep learning architecture with a novel loss function, which learns a feature space for materials that correlates with such perceived appearance similarity. Our evaluation shows that our model outperforms existing metrics. Last, we demonstrate several applications enabled by our metric, including appearance-based search for material suggestions, database visualization, clustering and summarization, and gamut mapping.

Idioma: Inglés

DOI: 10.1145/3306346.3323036

Año: 2019

Publicado en: ACM TRANSACTIONS ON GRAPHICS 38, 4 (2019), 135 [12 pp.]
ISSN: 0730-0301

Factor impacto JCR: 5.084 (2019)

Categ. JCR: COMPUTER SCIENCE, SOFTWARE ENGINEERING rank: 8 / 107 = 0.075 (2019) - Q1 - T1

Factor impacto SCIMAGO: 4.014 - Computer Graphics and Computer-Aided Design (Q1)

Financiación: info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2016-78753-P
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2016-79710-P

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)