Visual Clustering based on Kernel Sparse Representation on Grassmann Manifolds
文献类型：会议论文
| 作者 | Liu TC(刘天赐); Shi ZL(史泽林) ; Liu YP(刘云鹏)
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| 出版日期 | 2017 |
| 会议名称 | 7th Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (IEEE-CYBER 2017) |
| 会议日期 | July 31 - August 4, 2017 |
| 会议地点 | Hawaii, USA |
| 关键词 | visual clustering Grassmann manifold sparse representation kernel method |
| 页码 | 920-925 |
| 通讯作者 | Liu TC(刘天赐) |
| 中文摘要 | 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. In this paper, we propose a novel algorithm termed as kernel sparse subspace clustering on the Grassmann manifold (GKSSC) which embeds the Grassmann manifold into a Reproducing Kernel Hilbert Space (RKHS) 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, experimental results of clustering accuracy on the prevalent public dataset outperform state-of-the-art algorithms by more than 90 percent and the robustness of our algorithm is demonstrated as well. |
| 产权排序 | 1 |
| 会议录 | 7th Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (IEEE-CYBER 2017)
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5386-0489-2 |
| 源URL | [http://ir.sia.cn/handle/173321/21302]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 作者单位 | 1.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016 2.University of Chinese Academy of Sciences, Beijing 100049 3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016 4.The Key Lab of Image Understanding and Computer Vision, Liaoning Province, Shenyang 110016 |
| 推荐引用方式 GB/T 7714 | Liu TC,Shi ZL,Liu YP. Visual Clustering based on Kernel Sparse Representation on Grassmann Manifolds[C]. 见:7th Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (IEEE-CYBER 2017). Hawaii, USA. July 31 - August 4, 2017. |
入库方式： OAI收割
来源：沈阳自动化研究所
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