Optimal sampling of visual information for lightness judgments
Author(s) -
Matteo Toscani,
Matteo Valsecchi,
Karl R. Gegenfurtner
Publication year - 2013
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1216954110
Subject(s) - luminance , computer vision , artificial intelligence , lightness , computer science , gaze , object (grammar) , eye tracking , psychophysics , eye movement , mathematics , psychology , perception , neuroscience
The variable resolution and limited processing capacity of the human visual system requires us to sample the world with eye movements and attentive processes. Here we show that where observers look can strongly modulate their reports of simple surface attributes, such as lightness. When observers matched the color of natural objects they based their judgments on the brightest parts of the objects; at the same time, they tended to fixate points with above-average luminance. When we forced participants to fixate a specific point on the object using a gaze-contingent display setup, the matched lightness was higher when observers fixated bright regions. This finding indicates a causal link between the luminance of the fixated region and the lightness match for the whole object. Simulations with rendered physical lighting show that higher values in an object's luminance distribution are particularly informative about reflectance. This sampling strategy is an efficient and simple heuristic for the visual system to achieve accurate and invariant judgments of lightness.
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