Multiple discriminant analysis for collaborative representation-based classification
作者：
Highlights：
• A novel dimensionality reduction method for collaborative representation-based classification is proposed.
• The discriminant analysis and binarization technique are used to extract more informative features.
• A novel trace ratio algorithm is adopted to solve the proposed objective function.
• The convergence is proved and the time complexity is analyzed.
• Several experiments are conducted to show the effectiveness of the proposed method.
摘要
•A novel dimensionality reduction method for collaborative representation-based classification is proposed.•The discriminant analysis and binarization technique are used to extract more informative features.•A novel trace ratio algorithm is adopted to solve the proposed objective function.•The convergence is proved and the time complexity is analyzed.•Several experiments are conducted to show the effectiveness of the proposed method.
论文关键词：Collaborative representation,Orthogonal discriminative projection,Face recognition,Binary classification
论文评审过程：Received 11 December 2019, Revised 21 October 2020, Accepted 2 January 2021, Available online 7 January 2021, Version of Record 14 January 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2021.107819
