000117338 001__ 117338
000117338 005__ 20230519145507.0
000117338 0247_ $$2doi$$a10.1167/JOV.21.5.16
000117338 0248_ $$2sideral$$a126108
000117338 037__ $$aART-2021-126108
000117338 041__ $$aeng
000117338 100__ $$aDelanoy J.$$uUniversidad de Zaragoza
000117338 245__ $$aPerception of material appearance:Aa comparison between painted and rendered images
000117338 260__ $$c2021
000117338 5060_ $$aAccess copy available to the general public$$fUnrestricted
000117338 5203_ $$aPainters are masters in replicating the visual appearance of materials.While the perception of material appearance is not yet fully understood, painters seem to have acquired an implicit understanding of the key visual cues that we need to accurately perceive material properties. In this study, we directly compare the perception of material properties in paintings and in renderings by collecting professional realistic paintings of rendered materials. From both type of images, we collect human judgments of material properties and compute a variety of image features that are known to reflect material properties. Our study reveals that, despite important visual differences between the two types of depiction, material properties in paintings and renderings are perceived very similarly and are linked to the same image features. This suggests that we use similar visual cues independently of the medium and that the presence of such cues is sufficient to provide a good appearance perception of the materials. Copyright 2021 The Authors
000117338 536__ $$9info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON$$9info:eu-repo/grantAgreement/EC/H2020/765121/EU/DyViTo: Dynamics in Vision and Touch - the look and feel of stuff/DyViTo$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 765121-DyViTo$$9info:eu-repo/grantAgreement/EC/H2020/956585/EU/Predictive Rendering In Manufacture and Engineering/PRIME$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956585-PRIME
000117338 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000117338 590__ $$a2.004$$b2021
000117338 592__ $$a0.79$$b2021
000117338 594__ $$a3.2$$b2021
000117338 591__ $$aOPHTHALMOLOGY$$b44 / 62 = 0.71$$c2021$$dQ3$$eT3
000117338 593__ $$aSensory Systems$$c2021$$dQ2
000117338 593__ $$aOphthalmology$$c2021$$dQ2
000117338 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000117338 700__ $$0(orcid)0000-0002-7796-3177$$aSerrano A.$$uUniversidad de Zaragoza
000117338 700__ $$0(orcid)0000-0003-0060-7278$$aMasia B.$$uUniversidad de Zaragoza
000117338 700__ $$0(orcid)0000-0002-7503-7022$$aGutierrez D.$$uUniversidad de Zaragoza
000117338 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000117338 773__ $$g21, 5 (2021), 16 [24 pp]$$pJ. Vision$$tJournal of Vision$$x1534-7362
000117338 8564_ $$s3791542$$uhttps://zaguan.unizar.es/record/117338/files/texto_completo.pdf$$yVersión publicada
000117338 8564_ $$s3162580$$uhttps://zaguan.unizar.es/record/117338/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000117338 909CO $$ooai:zaguan.unizar.es:117338$$particulos$$pdriver
000117338 951__ $$a2023-05-18-15:06:30
000117338 980__ $$aARTICLE