Kernel sparse representation on Grassmann manifolds for visual clustering | |
Liu TC(刘天赐)1,2![]() ![]() ![]() | |
Department | 光电信息技术研究室 |
Source Publication | Optical Engineering
![]() |
ISSN | 0091-3286 |
2018 | |
Volume | 57Issue:5Pages:1-10 |
Indexed By | SCI ; EI |
EI Accession number | 20182105218002 |
WOS ID | WOS:000435435300013 |
Contribution Rank | 1 |
Funding Organization | National Natural Science Foundation of China ; Common Technical Project of Equipment Development Department |
Keyword | Grassmann Manifold Visual Clustering Sparse Representation Kernel Method |
Abstract | Image sets and videos can be modeled as subspaces, which are actually points on Grassmann manifolds. Clustering of such visual data lying on Grassmann manifolds is a hard issue based on the fact that the state-of-The-Art methods are only applied to vector space instead of non-Euclidean geometry. Although there exist some clustering methods for manifolds, the desirable method for clustering on Grassmann manifolds is lacking. We propose an algorithm termed as kernel sparse subspace clustering on the Grassmann manifold, which embeds the Grassmann manifold into a reproducing kernel Hilbert space by an appropriate Gaussian projection kernel. This kernel is applied to obtain kernel sparse representations of data on Grassmann manifolds utilizing the self-expressive property and exploiting the intrinsic Riemannian geometry within data. Although the Grassmann manifold is compact, the geodesic distances between Grassmann points are well measured by kernel sparse representations based on linear reconstruction. With the kernel sparse representations, clustering results of experiments on three prevalent public datasets outperform a number of existing algorithms and the robustness of our algorithm is demonstrated as well. |
Language | 英语 |
WOS Subject | Optics |
WOS Keyword | CLASSIFICATION ; SUBSPACES |
WOS Research Area | Optics |
Funding Project | National Natural Science Foundation of China[61540069] ; Common Technical Project of Equipment Development Department[Y6K4250401] |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.sia.cn/handle/173321/21875 |
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, China 2.University of Chinese Academy of Sciences, Beijing, China 3.Key Laboratory of Opto-Electronic Information Processing, Shenyang, China |
Recommended Citation GB/T 7714 | Liu TC,Shi ZL,Liu YP. Kernel sparse representation on Grassmann manifolds for visual clustering[J]. Optical Engineering,2018,57(5):1-10. |
APA | Liu TC,Shi ZL,&Liu YP.(2018).Kernel sparse representation on Grassmann manifolds for visual clustering.Optical Engineering,57(5),1-10. |
MLA | Liu TC,et al."Kernel sparse representation on Grassmann manifolds for visual clustering".Optical Engineering 57.5(2018):1-10. |
Files in This Item: | ||||||
File Name/Size | DocType | Version | Access | License | ||
Kernel sparse repres(1780KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | View Application Full Text |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment