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Beyond scattering and absorption: Perceptual unmixing of translucent liquids
Author(s) -
Alice Caitlin Chadwick,
George Cox,
Hannah E. Smithson,
Robert W. Kentridge
Publication year - 2018
Publication title -
journal of vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.126
H-Index - 113
ISSN - 1534-7362
DOI - 10.1167/18.11.18
Subject(s) - scattering , perception , absorption (acoustics) , stimulus (psychology) , biological system , optics , materials science , chemistry , mathematics , artificial intelligence , physics , computer science , psychology , cognitive psychology , biology , neuroscience
Is perception of translucence based on estimations of scattering and absorption of light or on statistical pseudocues associated with familiar materials? We compared perceptual performance with real and computer-generated stimuli. Real stimuli were glasses of milky tea. Milk predominantly scatters light and tea absorbs it, but since the tea absorbs less as the milk concentration increases, the effects of milkiness and strength on scattering and absorption are not independent. Conversely, computer-generated stimuli were glasses of "milky tea" in which absorption and scattering were independently manipulated. Observers judged tea concentrations regardless of milk concentrations, or vice versa. Maximum-likelihood conjoint measurement was used to estimate the contributions of each physical component-concentrations of milk and tea, or amounts of scattering and absorption-to perceived milkiness or tea strength. Separability of the two physical dimensions was better for real than for computer-generated teas, suggesting that interactions between scattering and absorption were correctly accounted for in perceptual unmixing, but unmixing was always imperfect. Since the real and rendered stimuli represent different physical processes and therefore differ in their image statistics, perceptual judgments with these stimuli allowed us to identify particular pseudocues (presumably learned with real stimuli) that explain judgments with both stimulus sets.

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