Abstract
The effect of aging varies in different facial regions. The significance of regions’ age related changes also differs in each age range. In this paper, an efficient subset is selected from all possible rectangle regions in the face image to form a global ensemble on the whole age range. Age range-based selective ensembles are also formed in a similar way. Based on those selective ensembles, a two-step selective region ensemble method is proposed for age estimation. In this framework, the first step is using the global ensemble to give a prediction of possible age range. The second step is to use the ensemble on the predicted age range to make a final estimation. Experiments show that using selective region ensemble can improve age estimation performance, and age range-based selective region ensemble is even superior to the global ensemble.
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Ben, S., Su, G., Wu, Y. (2008). A Two-Step Selective Region Ensemble for Facial Age Estimation. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_75
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DOI: https://doi.org/10.1007/978-3-540-85984-0_75
Publisher Name: Springer, Berlin, Heidelberg
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