关键词: 子空间聚类, 子空间结构化低秩, 相似度, 判别性, 一致性

Abstract: A new subspace structured low rank regularity is defined. Combining with the subspace Structured Sparse Subspace Clustering method（SSSC）, a new unified optimization model is given. The new model uses the estimated cluster membership of the samples and the affinity of the samples to guide each other so that the affinity possesses both discrimination and coherence and the cluster membership have coherence property. The discrimination of the affinity tends to segment data from different subspaces into different clusters while the coherence tends to group data from the same subspace into the same cluster. Experiments show that the proposed method outperforms the state-of-the-art two-stage methods and the SSSC method.

Key words: subspace clustering, subspace structured low rank, affinity, discrimination, coherence