A general subspace ensemble learning framework via totally-corrective boosting and tensor-based and local patch-based extensions for gait recognition

作者：

Highlights：

• A subspace ensemble learning via boosting is proposed for gait recognition.

• Three triplet building methods are proposed to improve the learning efficacy.

• The tensor-based extension is proposed to solve the tensor data.

• Another local patch-based extension solves the local patch-based learning problem.

摘要

Highlights•A subspace ensemble learning via boosting is proposed for gait recognition.•Three triplet building methods are proposed to improve the learning efficacy.•The tensor-based extension is proposed to solve the tensor data.•Another local patch-based extension solves the local patch-based learning problem.

论文关键词：Subspace learning,Boosting,Ensemble learning,Pattern recognition,Gait recognition

论文评审过程：Received 28 May 2016, Revised 6 December 2016, Accepted 2 January 2017, Available online 10 January 2017, Version of Record 12 March 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.01.003