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<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>doi:10.1167/JOV.21.5.16</dc:identifier><dc:language>eng</dc:language><dc:creator>Delanoy J.</dc:creator><dc:creator>Serrano A.</dc:creator><dc:creator>Masia B.</dc:creator><dc:creator>Gutierrez D.</dc:creator><dc:title>Perception of material appearance:Aa comparison between painted and rendered images</dc:title><dc:identifier>ART-2021-126108</dc:identifier><dc:description>Painters 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</dc:description><dc:date>2021</dc:date><dc:source>http://zaguan.unizar.es/record/117338</dc:source><dc:doi>10.1167/JOV.21.5.16</dc:doi><dc:identifier>http://zaguan.unizar.es/record/117338</dc:identifier><dc:identifier>oai:zaguan.unizar.es:117338</dc:identifier><dc:relation>info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON</dc:relation><dc:relation>This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON</dc:relation><dc:relation>info:eu-repo/grantAgreement/EC/H2020/765121/EU/DyViTo: Dynamics in Vision and Touch - the look and feel of stuff/DyViTo</dc:relation><dc:relation>This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 765121-DyViTo</dc:relation><dc:relation>info:eu-repo/grantAgreement/EC/H2020/956585/EU/Predictive Rendering In Manufacture and Engineering/PRIME</dc:relation><dc:relation>This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956585-PRIME</dc:relation><dc:identifier.citation>Journal of Vision 21, 5 (2021), 16 [24 pp]</dc:identifier.citation><dc:rights>by</dc:rights><dc:rights>http://creativecommons.org/licenses/by/3.0/es/</dc:rights><dc:rights>info:eu-repo/semantics/openAccess</dc:rights></dc:dc>

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