Joint Normalization and Dimensionality Reduction on Grassmannian: A Generalized Perspective | |
Liu TC(刘天赐)1,2![]() ![]() ![]() | |
Department | 光电信息技术研究室 |
Source Publication | IEEE Signal Processing Letters
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ISSN | 1070-9908 |
2018 | |
Volume | 25Issue:6Pages:858-862 |
Indexed By | SCI ; EI |
EI Accession number | 20181705055201 |
WOS ID | WOS:000432030000001 |
Contribution Rank | 1 |
Keyword | Image-set Recognition Grassmann Manifold Dimensionality Reduction Grassmannian Optimization |
Abstract | This paper proposes a generalized framework with joint normalization that learns lower-dimensional subspaces with maximum discriminative power by using Riemannian geometry. We model the similarity/dissimilarity between subspaces using various metrics defined on Grassmannian and formulate dimensionality reduction as a non-linear constraint optimization problem considering the orthogonalization. To obtain the linear mapping, we derive the components required to perform Riemannian optimization from the original Grassmannian through an orthonormal projection. We respect the Riemannian geometry of the Grassmann manifold and search for this projection directly from one Grassmann manifold to another face-to-face without any additional transformations. In this natural geometry-aware approach, any metric on the Grassmann manifold can theoretically reside in our model . We combine five metrics with our model, and the learning process is treated as an unconstrained optimization problem on a Grassmann manifold. Experiments on several datasets demonstrate that our approach leads to a significant accuracy gain over state-of-the-art methods. |
Language | 英语 |
WOS Subject | Engineering, Electrical & Electronic |
WOS Keyword | RECOGNITION ; MANIFOLDS ; GEOMETRY |
WOS Research Area | Engineering |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.sia.cn/handle/173321/21874 |
Collection | 光电信息技术研究室 |
Corresponding Author | Liu TC(刘天赐) |
Affiliation | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016 2.University of Chinese Academy of Sciences, Beijing 100049 3.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016 |
Recommended Citation GB/T 7714 | Liu TC,Shi ZL,Liu YP. Joint Normalization and Dimensionality Reduction on Grassmannian: A Generalized Perspective[J]. IEEE Signal Processing Letters,2018,25(6):858-862. |
APA | Liu TC,Shi ZL,&Liu YP.(2018).Joint Normalization and Dimensionality Reduction on Grassmannian: A Generalized Perspective.IEEE Signal Processing Letters,25(6),858-862. |
MLA | Liu TC,et al."Joint Normalization and Dimensionality Reduction on Grassmannian: A Generalized Perspective".IEEE Signal Processing Letters 25.6(2018):858-862. |
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Joint Normalization (712KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text |
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