Simultaneous learning of reduced prototypes and local metric for image set classification
作者：
Highlights：
• A simultaneous prototypes and local metric learning algorithm is proposed.
• The approach is used in biometrics and object recognition based on image set.
• Learned prototypes dramatically reduces the storage and time costs.
• Learned local metric significantly improves the discrimination ability of a set.
• Experimental results of our method superior/comparable to the literatures.
摘要
•A simultaneous prototypes and local metric learning algorithm is proposed.•The approach is used in biometrics and object recognition based on image set.•Learned prototypes dramatically reduces the storage and time costs.•Learned local metric significantly improves the discrimination ability of a set.•Experimental results of our method superior/comparable to the literatures.
论文关键词：Image set classification,Prototype learning,Metric learning,Face recognition,Expert system
论文评审过程：Received 24 July 2018, Revised 19 May 2019, Accepted 19 May 2019, Available online 24 May 2019, Version of Record 6 June 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.05.025
