Visualization of the first two principal components (PCs) of face shape (upper panel) and face texture (lower panel).

<p>The individual PC scores for these shape and texture features are plotted in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169336#pone.0169336.g003" target="_blank">Fig 3</a>. The reconstructed faces correspond to a deviation of 0.5 units (Procrustes distance) and 20,000 units from the mean shape and mean texture, respectively, which approximately corresponds to the occurring range of variation along PC1 and to a twofold extrapolation of this range along PC 2.</p

Landmark scheme.

<p>The landmarks and semilandmarks used for the shape analysis (black circles) and the image warping (grey disks) are shown on the average face texture deformed to the average face shape.</p

Regressions of shape (upper panel), texture (middle panel), as well as both together (lower panel) on BMI.

<p>The reconstructed faces represent the average shapes and textures predicted for BMI 15, 23, and 31, respectively, based on these regressions. These are ±2 standard deviations around the average BMI of 23 and approximately represent the range of variation observed in our sample. The left-most and right-most faces in the figure are twofold extrapolations of this range; they correspond to deviations of ±4 standard deviations from the mean and to (hypothetical) BMIs of 7 and 39.</p

Regression of facial texture on BMI, visualized for each color channel (R, G, B) separately.

<p>In contrast to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169336#pone.0169336.g005" target="_blank">Fig 5</a>, here the RGB values of each pixel were corrected to keep brightness constant (i.e., they were mean-centered separately for each pixel) to focus on the association of hue with BMI.</p

Descriptive statistics for body mass index (BMI) and waist-to-hip ratio (WHR): mean, standard deviation, range (min-max), and the three quartiles.

<p>Descriptive statistics for body mass index (BMI) and waist-to-hip ratio (WHR): mean, standard deviation, range (min-max), and the three quartiles.</p

Landmarks, stature, and masculinity ratings for 45 human faces

Females_21_70lms.txt: x and y coordinates of 70 landmarks measured on 21 female faces (21x140 data matrix) Males_24_70lms: x and y coordinates of 70 landmarks measured on 24 male faces (24x140 data matrix) Scale_factor_females.txt: scale factor of landmark coordinates for the female faces. Scale_factor_males.txt: scale factor of landmark coordinates for the male faces. Body_height_males_cm.txt: Measures of stature for the 24 male individuals (in cm). Perceived_masculinity.txt: Average masculinity ratings for the 24 male faces (range from 0 to 80)

Scree plots.

<p>Scree plots for (A) face shape and (B) face texture, showing the fractions of variance accounted for by the corresponding principal components.</p

The statistical distribution of two morphometric variables for two groups of individuals (males and females) is shown by two equal frequency ellipses and the corresponding means.

<p>(a) The mean difference vector (solid line) is spanned by the two mean configurations. The discriminant function (dashed line) maximizes the squared distance between the group means relative to the variation of the scores within the groups. When the two covariance matrices are the same (as in this example), it is the optimal direction to discriminate the two groups and to classify individuals with unknown group membership. (b) The mean difference vector can be decomposed into an allometric component (which, for many morphometric data sets, is close to the direction of maximum variance within the groups) and a non-allometric component (orthogonal to the allometric direction).</p

Landmark configuration used for studying face shape and perceived masculinity.

<p>(a) Face with the 33 landmarks (open circles) and 37 semilandmarks (filled circles) used in the morphometric analysis. (b) The shape features determining perceived masculinity are visualized by deformation grids from the mean shape to shapes predicted for deviations of ±20 rating scores from the average.</p

Sexual dimorphism is visualized by deformation grids between average female and average male facial shape, together with two-fold extrapolations of these shape differences.

<p>Sexual dimorphism is visualized by deformation grids between average female and average male facial shape, together with two-fold extrapolations of these shape differences.</p