Complete canonical correlation analysis with application to multi-view gait recognition

作者：

Highlights：

• We overcome the shortcomings of CCA when dealing with high-dimensional matrix.

• The singularity of generalized eigenvalue problem in CCA is overcome naturally.

• The important discriminative information is preserved completely in our algorithm.

• Our scheme learns stable and complete solutions.

• The multi-view gait recognition is achieved based on our method.

摘要

Highlights•We overcome the shortcomings of CCA when dealing with high-dimensional matrix.•The singularity of generalized eigenvalue problem in CCA is overcome naturally.•The important discriminative information is preserved completely in our algorithm.•Our scheme learns stable and complete solutions.•The multi-view gait recognition is achieved based on our method.

论文关键词：Canonical correlation analysis,Multi-view learning,Gait recognition

论文评审过程：Received 23 October 2014, Revised 21 May 2015, Accepted 12 August 2015, Available online 21 August 2015, Version of Record 5 November 2015.

论文官网地址：https://doi.org/10.1016/j.patcog.2015.08.011