Using fuzzy least squares support vector machine with metric learning for object tracking

作者：

Highlights：

• A new FLS-SVM-ML algorithm is proposed.

• A two-stage iterative process is used to solve the FLS-SVM-ML problem.

• A tracking algorithm based on FLS-SVM-ML is presented.

• Experimental results demonstrate the state-of-the-art tracking performance.

摘要

•A new FLS-SVM-ML algorithm is proposed.•A two-stage iterative process is used to solve the FLS-SVM-ML problem.•A tracking algorithm based on FLS-SVM-ML is presented.•Experimental results demonstrate the state-of-the-art tracking performance.

论文关键词：Object tracking,Metric learning,Fuzzy least squares support vector machine with metric learning(FLS-SVM-ML)

论文评审过程：Available online 6 July 2018, Version of Record 17 July 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.07.012