Facial recognition system image by analyzing multiple facial regions and details. It consists of a non-linear regression model that maps a specific thermal image into a corresponding visible facial image and an optimization issue that projects the latent projection back into the image space. ARL scientists have noted that the approach works by combining global information (i.e. features across the entire face) with local information (i.e. features regarding the eyes, nose, and mouth). In addition to enhancing the discriminability of the synthesized image, the facial recognition system can be used to transform a thermal face signature into a refined visible image of a
Facial symmetry associated with the symmetry of the face. Hormones such as testosterone and estrogen are believed to be associated with developmental processes and growth of facial features during puberty and as a result are hypothesized to be the cause for individual differences in the implications associated with facial symmetry. Facial bilateral symmetry is measured via fluctuating asymmetry of the face comparing random differences in facial features of the two sides of the face that develop and accumulate throughout one's lifetime as a result of stressors. Facial symmetry has been shown to have an effect of ratings of attractiveness in human faces.