A smile can reveal your age: enabling facial dynamics in age estimation

  • Authors:
  • Hamdi Dibeklioğlu;Theo Gevers;Albert Ali Salah;Roberto Valenti

  • Affiliations:
  • University of Amsterdam, Amsterdam, Netherlands;University of Amsterdam, Amsterdam, Netherlands;Bogazici University, Istanbul, Turkey;University of Amsterdam, Amsterdam, Netherlands

  • Venue:
  • Proceedings of the 20th ACM international conference on Multimedia
  • Year:
  • 2012

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Abstract

Estimation of a person's age from the facial image has many applications, ranging from biometrics and access control to cosmetics and entertainment. Many image-based methods have been proposed for this problem. In this paper, we propose a method for the use of dynamic features in age estimation, and show that 1) the temporal dynamics of facial features can be used to improve image-based age estimation; 2) considered alone, static image-based features are more accurate than dynamic features. We have collected and annotated an extensive database of face videos from 400 subjects with an age range between 8 and 76, which allows us to extensively analyze the relevant aspects of the problem. The proposed system, which fuses facial appearance and expression dynamics, performs with a mean absolute error of 4.81 (4.87) years. This represents a significant improvement of accuracy in comparison to the sole use of appearance-based features.