Robust subspace clustering based on inter-cluster correlation reduction by low rank representation
作者：
Highlights：
• A method for dealing with the inter-cluster correlation of subspace clustering.
• The new dictionary is reconstructed by detecting the inter-cluster correlation.
• Increasing of signal noise ratio causes the inter-cluster correlation obvious.
• The subspace clustering algorithm is extended by preprocessing on unaligned data.
• The experimental results on face and texture datasets verify the proposed method.
摘要
•A method for dealing with the inter-cluster correlation of subspace clustering.•The new dictionary is reconstructed by detecting the inter-cluster correlation.•Increasing of signal noise ratio causes the inter-cluster correlation obvious.•The subspace clustering algorithm is extended by preprocessing on unaligned data.•The experimental results on face and texture datasets verify the proposed method.
论文关键词：Subspace clustering,Inter-cluster correlation,Low rank model,Preprocessing
论文评审过程：Received 27 September 2019, Revised 23 December 2020, Accepted 3 January 2021, Available online 9 January 2021, Version of Record 14 January 2021.
论文官网地址：https://doi.org/10.1016/j.image.2021.116137
