The relative contribution of color and material in object selection

Abstract

Object perception is inherently multidimensional: information about color, material, texture and shape all guide how we interact with objects. We developed a paradigm that quantifies how two object properties (color and material) combine in object selection. On each experimental trial, observers viewed three blob-shaped objects—the target and two tests—and selected the test that was more similar to the target. Across trials, the target object was fixed, while the tests varied in color (across 7 levels) and material (also 7 levels, yielding 49 possible stimuli). We used an adaptive trial selection procedure (Quest+) to present, on each trial, the stimulus test pair that is most informative of underlying processes that drive selection. We present a novel computational model that allows us to describe observers’ selection data in terms of (1) the underlying perceptual stimulus representation and (2) a color-material weight, which quantifies the relative importance of color vs. material in selection. We document large individual differences in the color-material weight across the 12 observers we tested. Furthermore, our analyses reveal limits on how precisely selection data simultaneously constrain perceptual representations and the color-material weight. These limits should guide future efforts towards understanding the multidimensional nature of object perception.

Estimating the perceived dimension of psychophysical stimuli using triplet accuracy and hypothesis testing

“…An approach related to MLDS but for multiple dimensions, maximum-likelihood conjoint measurement ( Ho et al., 2008 ), tries to obtain interpretable dimensions by additional assumptions (e.g. monotonicity and independence of perceived dimensions; Radonjić, Cottaris, & Brainard, 2019 ), whereas MDS and ordinal embedding is more exploratory in trying to find the scale that best fits the data.…”

“…Thus, an appropriate dimension estimation procedure should include the distribution or variation of the scale’s accuracy and provide an interpretable decision criterion—a typical application of a statistical test. Such tests have already been applied to scaling models; for example Radonjić et al. (2019) use a t-test on the cross-validated model fit of an maximum-likelihood conjoint measurement-like scaling model to decide between the Euclidean or city-block distance metrics.…”

What is cognition?

“…As we move towards experiments with complex naturalistic stimuli, neither objective nor subjective techniques have yet proven entirely satisfactory. As stimulus complexity increases, the increase in dimensionality causes diffi culties for using objective methods to make inferences about the underlying perceptual representations [9], results from subjective methods become more subject to individual variation as well as to differences in instructions provided to subjects [10], and the quality of the link between perceptual representations obtained using objective and subjective methods can break down [11]. Further work is needed to determine how to resolve these diffi culties.…”

Color and gloss constancy under diverse lighting environments

“…Despite these extensive investigations into color constancy and gloss constancy as separate domains, very few studies have simultaneously measured color and gloss constancy (lightness and gloss, Olkkonen & Brainard, 2010, Hansmann-Roth & Mamassian, 2017 gloss and hue variation between green and blue, Radonjić et al 2018, Radonjić et al 2019. No study has measured all dimensions of perceived color (hue, chroma and lightness) and gloss at the same time.…”