Limitations of Traditional Morphometrics in Research on the Attractiveness of Faces

By Holland, Erik | Psychonomic Bulletin & Review, June 2009 | Go to article overview

Limitations of Traditional Morphometrics in Research on the Attractiveness of Faces


Holland, Erik, Psychonomic Bulletin & Review


The traditional morphometrics approach to shape comparisons involves computing multiple interlandmark distances without taking into account the geometric configuration of the landmarks. A recent example of this approach is a study by Potter and Corneille (2008). They had participants rate the attractiveness of computer-generated European, African, and Asian male faces, and they computed the Euclidean distances between each face and the group prototypes. They found that faces are rated more attractive when they are closer to their group prototype. This letter addresses differing conclusions in the literature, the methodological shortcomings of Potter and Corneille, and another study that explored a similar topic, with a special focus on guiding future researchers around the pitfalls of traditional morphometrics.

Conclusions Different From Potter and Corneille's (2008)

In many non-European populations, the attractive face is less ethnic-looking and closer to European norms than the average. This has been documented for Korean- American women evaluated by their co-ethnics (Choe, Sclafani, Litner, Yu, & Romo, 2004) and also for the profile of African-Americans (Farrow, Zarrinnia, & Azizi, 1993; Martin, 1964; Polk et al., 1995; Sushner, 1977; Thomas, 1979; but see Sutter & Turley, 1998, for a null find). Aesthetic facial cosmetic surgeries in East Asians (Ahn, 2006; Dobke, Chung, & Takabe, 2006; Lam, 2005) and African-Americans (Rohrich & Muzaffar, 2003) also tend to cluster in the direction of European norms.

Rhodes et al. (2005) found that Eurasian faces obtained by morphing European and East Asian faces were rated more attractive than European or East Asian faces. To my knowledge, this is the only study that has documented a shift toward East Asian norms increasing the perceived attractiveness of European faces, but this study had numerous shortcomings. These authors had the participants rate composite face morphs, rather than individual faces, for attractiveness. Some adjustments for differences in face size need to be performed when morphing faces together: A common practice, also employed by Rhodes et al., is to equalize interpupillary distance. However, a single interlandmark distance is a poor approximation of face size. In one standard implementation for controlling for size, one computes the center of mass of a form with unit mass at each of its landmarks. This is known as the centroid. One obtains the centroid size by summing the squared distances of a form's landmarks from its centroid. Then, scaling all forms to the same centroid size adjusts for size.

Another problem with Rhodes et al. (2005) is that all groups of the faces used (European, Asian) should have had similar distributions of attractiveness and femininity with respect to the norms in the respective ethnic groups. This is because the average of attractive faces is rated more attractive than the average of nonattractive faces (Johnston & Oliver-Rodriguez, 1997; Perrett, May, & Yoshikawa, 1994), and the femininity of a woman's face is a much more powerful correlate of beauty than its prototypicality (Rhodes, 2006); the prototypical female face is at the 50th percentile of femininity among women. But we have no indications that these requirements are met in Rhodes et al., and they would be difficult to fulfill.

Yet another problem with Rhodes et al. (2005) is that when one uses face composites, one cannot readily assess the effect on attractiveness when faces across a range of attractiveness are transformed along ethnic lines. Furthermore, Rhodes et al. assumed face shapes of ethnically mixed offspring to be an average of the parental face shapes, but this is not true for the majority of face-shape variables (Martínez-Abadías et al., 2006).

Methodological Issues

Faces generated by FaceGen Modeller. Potter and Corneille (2008) generated faces using FaceGen Modeller (www.facegen. …

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