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Sensors 2016, 16(7), 994; doi:10.3390/s16070994

Strategic Decision-Making Learning from Label Distributions: An Approach for Facial Age Estimation

School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798
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Academic Editor: Fabrizio Lamberti
Received: 8 April 2016 / Revised: 20 June 2016 / Accepted: 21 June 2016 / Published: 28 June 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [1694 KB, uploaded 28 June 2016]   |  

Abstract

Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used. However, this methodology is deficient in its simple decision-making criterion: the final predicted age is only selected at the one with maximum description degree. In many cases, different age labels may have very similar description degrees. Consequently, blindly deciding the estimated age by virtue of the highest description degree would miss or neglect other valuable age labels that may contribute a lot to the final predicted age. In this paper, we propose a strategic decision-making label distribution learning algorithm (SDM-LDL) with a series of strategies specialized for different types of age label distribution. Experimental results from the most popular aging face database, FG-NET, show the superiority and validity of all the proposed strategic decision-making learning algorithms over the existing label distribution learning and other single-label learning algorithms for facial age estimation. The inner properties of SDM-LDL are further explored with more advantages. View Full-Text
Keywords: strategic decision-making; label distribution learning; facial image; age estimation strategic decision-making; label distribution learning; facial image; age estimation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhao, W.; Wang, H. Strategic Decision-Making Learning from Label Distributions: An Approach for Facial Age Estimation. Sensors 2016, 16, 994.

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