Kernel sparse representation on Grassmann manifolds for visual clustering
文献类型：期刊论文
| 作者 | Liu, Tianci1,2,3; Shi, Zelin1,2; Liu, Yunpeng1,2 |
| 刊名 | OPTICAL ENGINEERING
 |
| 出版日期 | 2018-05-01 |
| 卷号 | 57期号:5页码:10 |
| 关键词 | Grassmann manifold visual clustering sparse representation kernel method |
| ISSN号 | 0091-3286 |
| DOI | 10.1117/1.OE.57.5.053104 |
| 通讯作者 | Liu, Tianci(liutianci@sia.cn) |
| 英文摘要 | 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. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) |
| 资助项目 | National Natural Science Foundation of China[61540069] ; Common Technical Project of Equipment Development Department[Y6K4250401] |
| WOS研究方向 | Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:000435435300013 |
| 出版者 | SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS |
| 资助机构 | National Natural Science Foundation of China ; Common Technical Project of Equipment Development Department |
| 源URL | [http://ir.imr.ac.cn/handle/321006/128649]  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Liu, Tianci |
| 作者单位 | 1.Key Lab Optoelect Informat Proc, Shenyang, Liaoning, Peoples R China 2.Chinese Acad Sci, Shenyang Inst Automat, Shenyang, Liaoning, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Tianci,Shi, Zelin,Liu, Yunpeng. Kernel sparse representation on Grassmann manifolds for visual clustering[J]. OPTICAL ENGINEERING,2018,57(5):10. |
| APA | Liu, Tianci,Shi, Zelin,&Liu, Yunpeng.(2018).Kernel sparse representation on Grassmann manifolds for visual clustering.OPTICAL ENGINEERING,57(5),10. |
| MLA | Liu, Tianci,et al."Kernel sparse representation on Grassmann manifolds for visual clustering".OPTICAL ENGINEERING 57.5(2018):10. |
入库方式： OAI收割
来源：金属研究所
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