Beautiful people are invested by others with a plethora of desirable characteristics such as warmth, sensitivity, poise, and kindness. In our culture, being beautiful has its advantages, as we are a society prone to judge a book by its cover. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces. F3 and F4 generation faces look profoundly similar. Faces evolve to approximate the guidelines suggested by classical canon.
FACE MORPH AGE FULL
When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. Multivariate analysis identified a similar collection of morphometric measures. Univariate analysis identified nasal width, eyebrow arch height, and lip thickness as being significantly correlated with attractiveness scores. Histograms of attractiveness score distributions show a significant shift in the skew of each curve toward more attractive faces with each generation. Morphometric measurements were made of 33 specific features on each of the 150 synthetic faces, and correlated with attractiveness scores using univariate and multivariate analysis. All five generations (P-F4) were then scored by three focus groups: a) surgeons (n = 12), b) cosmetology students (n = 44), and c) undergraduate students (n = 44). The algorithm mimics natural selection by using the attractiveness score as the selection pressure the more attractive faces are more likely to morph. The F1 faces were scored by the focus group, and the process was repeated for a total of four iterations of the algorithm.
FACE MORPH AGE SOFTWARE
A genetic algorithm was used to select 30 new pairs from the parent generation, and these were morphed using software to produce a new first generation (F1) of faces. Then, a focus group of 17 trained volunteers (18–25 y) scored each face on an attractiveness scale ranging from 1 (unattractive) to 10 (attractive). Randomly selected images were used to produce a parent generation (P) of 30 synthetic faces using morphing software. Digital images were acquired of 250 female volunteers (18–25 y).
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