Multi-view common component discriminant analysis for cross-view classification

作者：

Highlights：

• We extract view-independent features to remove the view discrepancy.

• We integrate discriminant regularization to learn a discriminant subspace.

• We extend single-view local geometry preservation to multi-view scenario.

• We integrate local consistency regularization to learn a structured subspace.

摘要

•We extract view-independent features to remove the view discrepancy.•We integrate discriminant regularization to learn a discriminant subspace.•We extend single-view local geometry preservation to multi-view scenario.•We integrate local consistency regularization to learn a structured subspace.

论文关键词：Cross-view classification,Local geometry preservation,Multi-view learning,Subspace learning

论文评审过程：Received 15 May 2018, Revised 15 February 2019, Accepted 15 March 2019, Available online 15 March 2019, Version of Record 23 March 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.03.008