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.
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Liang et al. (2014) studied this question.
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