Abstract
Color serves both to segment a scene into objects and background and to identify objects. Although objects and surfaces usually contain multiple colors, humans can readily extract a representative color description, for instance, that tomatoes are red and bananas yellow. The study of color discrimination and identification has a long history, yet we know little about the formation of summary representations of multicolored stimuli. Here, we characterize the human ability to integrate hue information over space for simple color stimuli varying in the amount of information, stimulus size, and spatial configuration of stimulus elements. We show that humans are efficient at integrating hue information over space beyond what has been shown before for color stimuli. Integration depends only on the amount of information in the display and not on spatial factors such as element size or spatial configuration in the range measured. Finally, we find that observers spontaneously prefer a simple averaging strategy even with skewed color distributions. These results shed light on how human observers form summary representations of color and make a link between the perception of polychromatic surfaces and the broader literature of ensemble perception.
Highlights
How do we attribute the color red to an apple? Objects often appear to have one predominant color, their surfaces may contain substantial spatial variation in how they reflect wavelengths of light
In order to estimate the efficiency in extracting hue information from ensembles, we systematically vary the external noise and the number of samples available to the observer and estimate effective sampling through mathematical modeling
We find that observers use a vastly larger number of samples than previously estimated for color
Summary
How do we attribute the color red to an apple? Objects often appear to have one predominant color, their surfaces may contain substantial spatial variation in how they reflect wavelengths of light. Maule and Franklin (2016) estimated that observers only use as few as two samples in a 16-element hue array when judging average color. In order to estimate the efficiency in extracting hue information from ensembles, we systematically vary the external noise (variance of the hue distribution from which the stimuli are drawn) and the number of samples available to the observer and estimate effective sampling through mathematical modeling.
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