April 12, 2008

Breeding attractive faces in a computer

A nice paper which "breeded" attractive faces by using morphing and a genetic algorithm. The researchers created successive generations of faces by combining (with morphing) faces rated as attractive. They were able to create faces of increasing attractiveness in each subsequent generation.

I don't have the paper (send it to me if you do!), but a question is: does increasing attractiveness result from more averaging, or from the selection pressure imposed by raters? We do know that facial averaging has a beautifying effect: really attractive faces are not average, but average faces tend to be attractive. One could determine the effect of the selection pressure -above and beyond that of averaging- by comparing faces evolved under pressure with randomly bred faces.

Laryngoscope. 2008 Apr 7 [Epub ahead of print]

Evolving Attractive Faces Using Morphing Technology and a Genetic Algorithm: A New Approach to Determining Ideal Facial Aesthetics.

Wong BJ, Karimi K, Devcic Z, McLaren CE, Chen WP.

OBJECTIVES:: The objectives of this study were to: 1) determine if a genetic algorithm in combination with morphing software can be used to evolve more attractive faces; and 2) evaluate whether this approach can be used as a tool to define or identify the attributes of the ideal attractive face. STUDY DESIGN:: Basic research study incorporating focus group evaluations. METHODS:: Digital images were acquired of 250 female volunteers (18-25 y). Randomly selected images were used to produce a parent generation (P) of 30 synthetic faces using morphing software. 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). 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. The F1 faces were scored by the focus group, and the process was repeated for a total of four iterations of the algorithm. The algorithm mimics natural selection by using the attractiveness score as the selection pressure; the more attractive faces are more likely to morph. 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). 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. RESULTS:: The average facial attractiveness scores increased with each generation and were 3.66 (+0.60), 4.59 (+/-0.73), 5.50 (+/-0.62), 6.23 (+/-0.31), and 6.39 (+/-0.24) for P and F1-F4 generations, respectively. Histograms of attractiveness score distributions show a significant shift in the skew of each curve toward more attractive faces with each generation. Univariate analysis identified nasal width, eyebrow arch height, and lip thickness as being significantly correlated with attractiveness scores. Multivariate analysis identified a similar collection of morphometric measures. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. Faces evolve to approximate the guidelines suggested by classical canons. F3 and F4 generation faces look profoundly similar. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces. CONCLUSIONS:: The use of genetic algorithms in combination with a morphing software and traditional focus-group derived attractiveness scores can be used to evolve attractive synthetic faces. We have demonstrated that the evolution of attractive faces can be mimicked in software. Genetic algorithms and morphing provide a robust alternative to traditional approaches rooted in comparing attractiveness scores with a series of morphometric measurements in human subjects.



  1. I think my family looks nice already-at least for their kind of ethnicity they do......like McCall girls of the 70's. -God I love those McCall girls ! And they will continue to look good as long as they don't have sex with an ugly foreigner,as long as they keep Eugenics up and running -then they'll always look pretty! That's what I think.

  2. Most people look pretty good already if they stick with their own kind-I'm dead serious.I was hoping that DNA testing would allow participants to hook up with their own race to continue to make master race groups.Where as currently you have to pick any old strange dog you can find in the street then your kids look like old strange dogs too.

  3. Miz rand blowtown. Are you Jewish or German? Chosen Race or Master Race? Or is there another group, with similar ideas, I haven't yet heard about?


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