Calibrating facial morphs for use as stimuli in biological studies of social perception - PubMed
- ️Mon Jan 01 2018
Calibrating facial morphs for use as stimuli in biological studies of social perception
Sonja Windhager et al. Sci Rep. 2018.
Abstract
Studies of human social perception become more persuasive when the behavior of raters can be separated from the variability of the stimuli they are rating. We prototype such a rigorous analysis for a set of five social ratings of faces varying by body fat percentage (BFP). 274 raters of both sexes in three age groups (adolescent, young adult, senior) rated five morphs of the same averaged facial image warped to the positions of 72 landmarks and semilandmarks predicted by linear regression on BFP at five different levels (the average, ±2 SD, ±5 SD). Each subject rated all five morphs for maturity, dominance, masculinity, attractiveness, and health. The patterns of dependence of ratings on the BFP calibration differ for the different ratings, but not substantially across the six groups of raters. This has implications for theories of social perception, specifically, the relevance of individual rater scale anchoring. The method is also highly relevant for other studies on how biological facial variation affects ratings.
Conflict of interest statement
The authors declare no competing interests.
Figures

The face stimulus set (calibration sample) varied solely in the amounts of body fat percentage (BFP) associated with facial shape. From the geometric morphometric shape regression upon body fat percentage in female adolescents originally published in Windhager et al., landmark coordinates of five target configurations were computed for the sample average as well as the average plus and minus 2 and 5 standard deviations of BFP. The original photographs of the adolescents were then unwarped to these target configurations and averaged. Apparent changes along this progression in small features (e.g., eyebrow arching) are epiphenomena of the underlying regression of shape on BFP, a pattern showing large-scale integration. They are not experimentally controlled or otherwise manipulated features of the stimulus ordination per se.

Male participants’ rating of the five female adolescent morphs. The y-axes depict the range of the continuous rating scales. The x-axis bears the z-scored body fat percentage (z-BFP) of the five facial shapes driving the morphing. All scatterplots depict mean ± one standard deviation rating per stimulus, overlaid by a least-squares quadratic fit. There is high consistency in curve shape across the three age groups, i.e. within a row, and distinctness across the five rating scales, i.e. down the rows.

Female participants’ rating of the five female adolescent morphs. These fifteen scatterplots depict the original data of the female raters analogously to Fig. 2.

Selected curve prototypes. Calibrated stimuli allow fine-graded quantitative models of response patterns for the different rating scales. In our case, the individual ratings were best summarized by linear and quadratic regression fits. This figure highlights the different curve shapes resulting from the combination of our calibrated morphs upon BFP together with the request for five different ratings of each morph. While the absolute position (of the vertex) along the rating scale or the slope varies somewhat by rater sex and age group, the overall shape of the curve as depicted here is remarkably constant across the rows of Figs 2 and 3.
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References
-
- Martens, H. & Naes, T. Multivariate Calibration (Wiley, 1989).
-
- Schultz, D. P. & Schultz, S. E. A History of Modern Psychology, 10th edn. (Cengage Learning, 2011).
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