Structured general and specific multi-view subspace clustering

Wencheng Zhu, Jiwen Lu, Jie Zhou

Abstract: Highlights•We propose a structured general and specific multi-view subspace clustering method for image clustering.•The structural general representation matrix keeps the similarity relationship of data and the specific representation matrices exploit the diversity between different matrices.•We present an effective optimization algorithm to solve the proposed objective function.•Compared with most state-of-the-arts, experimental results demonstrate that our proposed methods obtain superior performances on four benchmark datasets.