Understanding gloss perception through the lens of art: Combining perception, image analysis, and painting recipes of 17th century painted grapes
Author(s) -
Francesca Di Cicco,
Maarten Wijntjes,
Sylvia C. Pont
Publication year - 2019
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/19.3.7
Subject(s) - gloss (optics) , painting , perception , contrast (vision) , art , artificial intelligence , computer science , computer vision , psychology , visual arts , materials science , neuroscience , composite material , coating
To understand the key image features that we use to infer the glossiness of materials, we analyzed the pictorial shortcuts used by 17th century painters to imitate the optical phenomenon of specular reflections when depicting grapes. Gloss perception of painted grapes was determined via a rating experiment. We computed the contrast, blurriness, and coverage of the grapes' highlights in the paintings' images, inspired by Marlow and Anderson (2013). The highlights were manually segmented from the images, and next the features contrast, coverage, and blurriness were semiautomatically quantified using self-defined algorithms. Multiple linear regressions of contrast and blurriness resulted in a predictive model that could explain 69% of the variance in gloss perception. No effect was found for coverage. These findings are in agreement with the instructions to render glossiness of grapes contained in a 17th century painting manual (Beurs, 1692/in press), suggesting that painting practice embeds knowledge about key image features that trigger specific material percepts.
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