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Kernel sparse representation on Grassmann manifolds for visual clustering
Liu TC(刘天赐)1,2; Shi ZL(史泽林)1,3; Liu YP(刘云鹏)1,3
作者部门光电信息技术研究室
关键词Grassmann Manifold Visual Clustering Sparse Representation Kernel Method
发表期刊Optical Engineering
ISSN0091-3286
2018
卷号57期号:5页码:1-10
收录类别SCI ; EI
EI收录号20182105218002
WOS记录号WOS:000435435300013
产权排序1
资助机构National Natural Science Foundation of China ; Common Technical Project of Equipment Development Department
摘要

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.

语种英语
WOS类目Optics
关键词[WOS]CLASSIFICATION ; SUBSPACES
WOS研究方向Optics
资助项目National Natural Science Foundation of China[61540069] ; Common Technical Project of Equipment Development Department[Y6K4250401]
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/21875
专题光电信息技术研究室
通讯作者Liu TC(刘天赐)
作者单位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
推荐引用方式
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.
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