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Material category of visual objects computed from specular image structure

Bibliographic Data

ID4686882
AuthorsAlexandra C Schmid (0000-0001-6555-3894, Justus-Liebig-Universität Gießen, corresponding author), Pascal Barla (0000-0003-2844-6656, Centre Inria de l'université de Bordeaux), Katja Doerschner (0000-0002-8364-800X, Justus-Liebig-Universität Gießen)
Year2023
Volume7
Issue7
Pages1152-1169
Publication date2023-06-29
Open AccessYes
TypeARTICLE
VenueNature Human Behaviour (JOURNAL)
Journal identifiersISSN: 2397-3374 • E-ISSN: 2397-3374
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1038/s41562-023-01601-0
PMID37386108
OpenAlexW2996825415
LanguageEN
Citations received1
References cited68

Recognizing materials and their properties visually is vital for successful interactions with our environment, from avoiding slippery floors to handling fragile objects. Yet there is no simple mapping of retinal image intensities to physical properties. Here, we investigated what image information drives material perception by collecting human psychophysical judgements about complex glossy objects. Variations in specular image structure-produced either by manipulating reflectance properties or visual features directly-caused categorical shifts in material appearance, suggesting that specular reflections provide diagnostic information about a wide range of material classes. Perceived material category appeared to mediate cues for surface gloss, providing evidence against a purely feedforward view of neural processing. Our results suggest that the image structure that triggers our perception of surface gloss plays a direct role in visual categorization, and that the perception and neural processing of stimulus properties should be studied in the context of recognition, not in isolation

Categorization · Computer vision · Optics · Perception · Physics · Specular reflection · Visual perception · Communication · Computer Science · Face Recognition and Perception · Materials Science · Neural dynamics and brain function · Neuroscience · Psychology · Visual perception and processing mechanisms · Artificial Intelligence

  • Unsupervised learning predicts human perception and misperception of gloss

    Open Access•Katherine R Storrs, Barton L Anderson et al.•Nature Human Behaviour•2021

  • The Psychophysics Toolbox

    David H Brainard•Spatial Vision•1997

  • Unsupervised learning predicts human perception and misperception of gloss

    Open Access•Katherine R Storrs, Barton L Anderson et al.•Nature Human Behaviour•2021

Citations per year0.2
Citation span2021 - 2021 (1)
Highly citedNo

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