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A Hierarchical Framework for Facial Age Estimation

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  • Yuyu Liang
  • Xianmei Wang
  • Li Zhang
  • Zhiliang Wang

Abstract

Age estimation is a complex issue of multiclassification or regression. To address the problems of uneven distribution of age database and ignorance of ordinal information, this paper shows a hierarchic age estimation system, comprising age group and specific age estimation. In our system, two novel classifiers, sequence k-nearest neighbor (SKNN) and ranking-KNN, are introduced to predict age group and value, respectively. Notably, ranking-KNN utilizes the ordinal information between samples in estimation process rather than regards samples as separate individuals. Tested on FG-NET database, our system achieves 4.97 evaluated by MAE (mean absolute error) for age estimation.

Suggested Citation

  • Yuyu Liang & Xianmei Wang & Li Zhang & Zhiliang Wang, 2014. "A Hierarchical Framework for Facial Age Estimation," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-8, April.
    • Handle: RePEc:hin:jnlmpe:242846
    DOI: 10.1155/2014/242846
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