Cross-view semantic projection learning for person re-identification
作者：
Highlights：
• We propose a novel feature transformation algorithm for person re-identification.
• The hand-crafted features are mapped into the common semantic space via view-specific semantic projection functions.
• The common intrinsic structure is explored via a shared semantic basis matrix.
• The association matrix is utilized to capture the optimal associations of the same persons.
• We further extend the CSPL algorithm for multi-view analysis.
摘要
•We propose a novel feature transformation algorithm for person re-identification.•The hand-crafted features are mapped into the common semantic space via view-specific semantic projection functions.•The common intrinsic structure is explored via a shared semantic basis matrix.•The association matrix is utilized to capture the optimal associations of the same persons.•We further extend the CSPL algorithm for multi-view analysis.
论文关键词：Person re-identification,Feature transformation,Semantic representation learning,Semantic projection learning
论文评审过程：Received 8 September 2016, Revised 6 March 2017, Accepted 17 April 2017, Available online 25 April 2017, Version of Record 21 November 2017.
论文官网地址：https://doi.org/10.1016/j.patcog.2017.04.022
