September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Absolute beauty ratings predict mean relative beauty ratings
Author Affiliations & Notes
  • Qihan Wu
    New York University, Department of Psychology
  • Aenne A Brielmann
    New York University, Department of Psychology
  • Denis G Pelli
    New York University, Department of Psychology
    New York University, Center for Neural Science
Journal of Vision September 2019, Vol.19, 98b. doi:https://doi.org/10.1167/19.10.98b
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      Qihan Wu, Aenne A Brielmann, Denis G Pelli; Absolute beauty ratings predict mean relative beauty ratings. Journal of Vision 2019;19(10):98b. doi: https://doi.org/10.1167/19.10.98b.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Can you compare the beauty of the Mona Lisa to Starry Night? Would your beauty ratings of single images predict your rating of their relative beauty? Twenty-five participants were tested with 14 OASIS images and 6 self-selected images. There were 2 tasks. In the relative task, each participant saw all possible two-image pairs twice, chose which image was more beautiful and rated by how much on a 1–9 scale. In the absolute task, they saw all 20 images randomly presented one by one 4 times and rated how much beauty they felt from each, 1–9. We find that the participants made consistent absolute and relative beauty judgments (absolute: test-retest r = 0.98, σ 2 = 0.29; relative: test-retest r = 0.84, σ2 = 1.37). We used absolute beauty ratings to predict relative beauty ratings by subtracting one image’s absolute beauty rating from the other’s. This simple model precisely predicts mean beauty difference ratings (r = 0.79) and 80% of the choices. Thus, the mean beauty difference ratings are predicted by mean absolute beauty ratings. But the variance in our data is 2.4 times as large as predicted by our model, suggesting a noisy comparison process.

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