Human Age Estimation Based on Locality and Ordinal Information
文献类型：期刊论文
| 作者 | Li, Changsheng1; Liu, Qingshan2; Dong, Weishan1; Zhu, Xiaobin3; Liu, Jing4 ; Lu, Hanqing4
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| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
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| 出版日期 | 2015-11-01 |
| 卷号 | 45期号:11页码:2522-2534 |
| 关键词 | Age estimation feature selection local manifold structure ordinal pattern semi-supervised learning |
| 英文摘要 | In this paper, we propose a novel feature selection-based method for facial age estimation. The face aging is a typical temporal process, and facial images should have certain ordinal patterns in the aging feature space. From the geometrical perspective, a facial image can be usually seen as sampled from a low-dimensional manifold embedded in the original high-dimensional feature space. Thus, we first measure the energy of each feature in preserving the underlying local structure information and the ordinal information of the facial images, respectively, and then we intend to learn a low-dimensional aging representation that can maximally preserve both kinds of information. To further improve the performance, we try to eliminate the redundant local information and ordinal information as much as possible by minimizing nonlinear correlation and rank correlation among features. Finally, we formulate all these issues into a unified optimization problem, which is similar to linear discriminant analysis in format. Since it is expensive to collect the labeled facial aging images in practice, we extend the proposed supervised method to a semi-supervised learning mode including the semi-supervised feature selection method and the semi-supervised age prediction algorithm. Extensive experiments are conducted on the FACES dataset, the Images of Groups dataset, and the FG-NET aging dataset to show the power of the proposed algorithms, compared to the state-of-the-arts. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | FACE RECOGNITION ; REGRESSION ; REPRESENTATION ; EXPRESSIONS ; FEATURES ; MANIFOLD ; IMAGES ; MODELS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000363233000013 |
| 公开日期 | 2016-02-26 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/10494]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 作者单位 | 1.IBM Res China, Beijing 100094, Peoples R China 2.Nanjing Univ Informat Sci & Technol, Sch Informat & Control, B DAT Lab, Nanjing 210044, Jiangsu, Peoples R China 3.Beijing Technol & Business Univ, Sch Comp & Informat Engn, Beijing 100048, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Changsheng,Liu, Qingshan,Dong, Weishan,et al. Human Age Estimation Based on Locality and Ordinal Information[J]. IEEE TRANSACTIONS ON CYBERNETICS,2015,45(11):2522-2534. |
| APA | Li, Changsheng,Liu, Qingshan,Dong, Weishan,Zhu, Xiaobin,Liu, Jing,&Lu, Hanqing.(2015).Human Age Estimation Based on Locality and Ordinal Information.IEEE TRANSACTIONS ON CYBERNETICS,45(11),2522-2534. |
| MLA | Li, Changsheng,et al."Human Age Estimation Based on Locality and Ordinal Information".IEEE TRANSACTIONS ON CYBERNETICS 45.11(2015):2522-2534. |
入库方式： OAI收割
来源：自动化研究所
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