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