標題: | SPARSE SUBSPACE CLUSTERING WITH SEQUENTIALLY ORDERED AND WEIGHTED L1-MINIMIZATION |
作者: | Wu, Jwo-Yuh Huang, Liang-Chi Yang, Ming-Hsun Chang, Ling-Hua Liu, Chun-Hung 交大名義發表 電信工程研究所 National Chiao Tung University Institute of Communications Engineering |
關鍵字: | Subspace clustering;sparse representation;compressive sensing |
公開日期: | 1-一月-2019 |
摘要: | Built on the sparse representation framework, sparse subspace clustering (SSC) received considerable attention in the recent years. Conventional SSC employs. l(1)-minimization based sparse regression for neighbor identification on a sample-by-sample basis, and is unaware of the neighbor information revealed by those already computed sparse representation vectors. To rid this drawback, this paper proposes a weighted. l(1)-minimization based sparse regression method, and an associated data ordering rule able to reflect the reliability of neighbor information for further enhancing the clustering accuracy. The selection of weighting coefficients for SSC is also discussed. Computer simulations using both the synthesis and real data are provided to evidence the effectiveness of the proposed method. |
URI: | http://hdl.handle.net/11536/154050 |
ISBN: | 978-1-5386-6249-6 |
ISSN: | 1522-4880 |
期刊: | 2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) |
起始頁: | 3387 |
結束頁: | 3391 |
顯示於類別: | 會議論文 |