A study on automatic age estimation using a large database

Guodong Guo, Guowang Mu, Yun Fu, Charles Dyer, Thomas S Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we study some problems related to human age estimation using a large database. First, we study the influence of gender on age estimation based on face representations that combine biologically-inspired features with manifold learning techniques. Second, we study age estimation using smaller gender and age groups rather than on all ages. Significant error reductions are observed in both cases. Based on these results, we designed three frameworks for automatic age estimation that exhibit high performance. Unlike previous methods that require manual separation of males and females prior to age estimation, our work is the first to estimate age automatically on a large database. Furthermore, a data fusion approach is proposed using one of the frameworks, which gives an age estimation error more than 40% smaller than previous methods.

Original languageEnglish (US)
Title of host publication2009 IEEE 12th International Conference on Computer Vision, ICCV 2009
Pages1986-1991
Number of pages6
DOIs
StatePublished - Dec 1 2009
Event12th International Conference on Computer Vision, ICCV 2009 - Kyoto, Japan
Duration: Sep 29 2009Oct 2 2009

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other12th International Conference on Computer Vision, ICCV 2009
CountryJapan
CityKyoto
Period9/29/0910/2/09

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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    Guo, G., Mu, G., Fu, Y., Dyer, C., & Huang, T. S. (2009). A study on automatic age estimation using a large database. In 2009 IEEE 12th International Conference on Computer Vision, ICCV 2009 (pp. 1986-1991). [5459438] (Proceedings of the IEEE International Conference on Computer Vision). https://doi.org/10.1109/ICCV.2009.5459438