Literature DB >> 28384658

Maximum likelihood difference scales represent perceptual magnitudes and predict appearance matches.

Christiane B Wiebel1, Guillermo Aguilar2, Marianne Maertens1.   

Abstract

One central problem in perception research is to understand how internal experiences are linked to physical variables. Most commonly, this relationship is measured using the method of adjustment, but this has two shortcomings: The perceptual scales that relate physical and perceptual variables are not measured directly, and the method often requires perceptual comparisons between viewing conditions. To overcome these problems, we measured perceptual scales of surface lightness using maximum likelihood difference scaling, asking observers only to compare the lightness of surfaces presented in the same context. Observers were lightness constant, and the perceptual scales qualitatively and quantitatively predicted perceptual matches obtained in a conventional adjustment experiment. Additionally, we show that a contrast-based model of lightness perception predicted 98% of the variance in the scaling and 88% in the matching data. We suggest that the predictive power was higher for scales because they are closer to the true variables of interest.

Mesh:

Year:  2017        PMID: 28384658     DOI: 10.1167/17.4.1

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  3 in total

1.  Toward reliable measurements of perceptual scales in multiple contexts.

Authors:  Guillermo Aguilar; Marianne Maertens
Journal:  J Vis       Date:  2020-04-09       Impact factor: 2.240

2.  Maximum likelihood estimation of difference scaling functions for suprathreshold judgments.

Authors:  Emily S Teti; Terece L Turton; Jonah M Miller; Roxana Bujack
Journal:  J Vis       Date:  2022-09-02       Impact factor: 2.004

3.  Conjoint measurement of perceived transparency and perceived contrast in variegated checkerboards.

Authors:  Guillermo Aguilar; Marianne Maertens
Journal:  J Vis       Date:  2022-02-01       Impact factor: 2.240

  3 in total

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