Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81055
Title: Multifeature Extreme Ordinal Ranking Machine for Facial Age Estimation
Authors: Zhao, Wei
Wang, Han
Huang, Guang-Bin
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2015
Source: Zhao, W., Wang, H., & Huang, G.-B. (2015). Multifeature Extreme Ordinal Ranking Machine for Facial Age Estimation. Mathematical Problems in Engineering, 2015, 840840-.
Series/Report no.: Mathematical Problems in Engineering
Abstract: Recently the state-of-the-art facial age estimation methods are almost originated from solving complicated mathematical optimization problems and thus consume huge quantities of time in the training process. To refrain from such algorithm complexity while maintaining a high estimation accuracy, we propose a multifeature extreme ordinal ranking machine (MFEORM) for facial age estimation. Experimental results clearly demonstrate that the proposed approach can sharply reduce the runtime (even up to nearly one hundred times faster) while achieving comparable or better estimation performances than the state-of-the-art approaches. The inner properties of MFEORM are further explored with more advantages.
URI: https://hdl.handle.net/10356/81055
http://hdl.handle.net/10220/39103
ISSN: 1024-123X
DOI: 10.1155/2015/840840
Rights: © 2015 Wei Zhao et al. 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.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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