Computers will be able to tell social traits from the face

In the current study, the researchers used a subset of these images, together with their labels, to "teach" the computer how to read a face, and tested the prediction accuracy using the rest of the images. Three traits, dominant, threatening and mean, were found to be predictable with accuracies between 91% and 96%. Additionally the study aimed to find what information is computationally useful for the prediction task. For example, they found that the area around the eyes contains more information about attractiveness, while the area around the mouth is more informative about extroversion.

The researchers also challenged their program's predictive ability against the faces of a number of celebrities; they found that their results are highly consistent with our general ideas about these public figures.

Citation: Rojas Q. M, Masip D, Todorov A, Vitria J (2011) Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models. PLoS ONE 6(8): e23323. doi:10.1371/journal.pone.0023323

Funding: This work was supported by the MICINN grant (Ministerio de Ciencia e Innovacio´n - Ministry of Science and Innovation, http://www.boe.es/boe/dias/2010/04/13/pdfs/BOE-A-2010-5939.pdf) TIN2009-14404-C02-01, the CONSOLIDER-INGENIO 2010 grant (CSD2007-00018) http://www.ingenio2010.es/contenido.asp?menu1=3&menu2=1&menu3=&dir=./02_instrumentos/02_Caracteristicas/01_CONSOLIDER&id=En(), and the National Science Foundation grant NSF 0823749. No additional external funding was received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist.

Link to the freely available article: http://www.plos.org/press/pone-05-08-rojas.pdf

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