Geometric facial gender scoring: objectivity of perception

PLoS One. 2014 Jun 12;9(6):e99483. doi: 10.1371/journal.pone.0099483. eCollection 2014.

Abstract

Gender score is the cognitive judgement of the degree of masculinity or femininity of a face which is considered to be a continuum. Gender scores have long been used in psychological studies to understand the complex psychosocial relationships between people. Perceptual scores for gender and attractiveness have been employed for quality assessment and planning of cosmetic facial surgery. Various neurological disorders have been linked to the facial structure in general and the facial gender perception in particular. While, subjective gender scoring by human raters has been a tool of choice for psychological studies for many years, the process is both time and resource consuming. In this study, we investigate the geometric features used by the human cognitive system in perceiving the degree of masculinity/femininity of a 3D face. We then propose a mathematical model that can mimic the human gender perception. For our experiments, we obtained 3D face scans of 64 subjects using the 3dMDface scanner. The textureless 3D face scans of the subjects were then observed in different poses and assigned a gender score by 75 raters of a similar background. Our results suggest that the human cognitive system employs a combination of Euclidean and geodesic distances between biologically significant landmarks of the face for gender scoring. We propose a mathematical model that is able to automatically assign an objective gender score to a 3D face with a correlation of up to 0.895 with the human subjective scores.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Algorithms
  • Discriminant Analysis
  • Face / anatomy & histology*
  • Female
  • Humans
  • Male
  • Models, Theoretical
  • Perception / physiology*
  • Sex Characteristics*
  • Young Adult

Grants and funding

This research was partly supported by Australian Research Council Discovery Grant DP110102399 and UWA Faculty of Engineering, Computing and Mathematics Development Grant. Syed Zulqarnain Gilani is supported by International Postgraduate Research Scholarship, and Faisal Shafait was supported by Australian Research Council grant LP110201008. The funding agencies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.