| A-Optimal Projection for Image Representation | |
He, Xiaofei1; Zhang, Chiyuan1; Zhang, Lijun2; Li, Xuelong3
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| 作者部门 | 光学影像学习与分析中心 |
| 2016-05-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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| ISSN | 0162-8828 |
| 卷号 | 38期号:5页码:1009-1015 |
| 产权排序 | 3 |
| 摘要 | We consider the problem of image representation from the perspective of statistical design. Recent studies have shown that images are possibly sampled from a low dimensional manifold despite of the fact that the ambient space is usually very high dimensional. Learning low dimensional image representations is crucial for many image processing tasks such as recognition and retrieval. Most of the existing approaches for learning low dimensional representations, such as principal component analysis (PCA) and locality preserving projections (LPP), aim at discovering the geometrical or discriminant structures in the data. In this paper, we take a different perspective from statistical experimental design, and propose a novel dimensionality reduction algorithm called A-Optimal Projection (AOP). AOP is based on a linear regression model. Specifically, AOP finds the optimal basis functions so that the expected prediction error of the regression model can be minimized if the new representations are used for training the model. Experimental results suggest that the proposed approach provides a better representation and achieves higher accuracy in image retrieval. |
| 文章类型 | Article |
| 关键词 | Dimensionality Reduction Optimal Design Image Representation |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1109/TPAMI.2015.2439252 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | NONLINEAR DIMENSIONALITY REDUCTION ; GEOMETRIC FRAMEWORK ; REGRESSION ; RETRIEVAL |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| 项目资助者 | National Basic Research Program of China (973 Program)(2012CB316400) ; National Program for Special Support of Top-Notch Young Professionals ; National Natural Science Foundation of China(61233011 ; 61125203) |
| WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000374164700013 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/28088 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Zhejiang Univ, Coll Comp Sci, State Key Lab CAD & CG, Hangzhou 310058, Zhejiang, Peoples R China 2.Nanjing Univ, Natl Key Lab Novel Software Technol, Nanjing 210023, Jiangsu, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr Opt IMagery Anal & Learning OPTIMAL, State key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Xiaofei,Zhang, Chiyuan,Zhang, Lijun,et al. A-Optimal Projection for Image Representation[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2016,38(5):1009-1015. |
| APA | He, Xiaofei,Zhang, Chiyuan,Zhang, Lijun,&Li, Xuelong.(2016).A-Optimal Projection for Image Representation.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,38(5),1009-1015. |
| MLA | He, Xiaofei,et al."A-Optimal Projection for Image Representation".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 38.5(2016):1009-1015. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| A-Optimal Projection（396KB） | 期刊论文 | 作者接受稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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