Joint prototype and metric learning for image set classification: Application to video face identification
作者：
Highlights：
• A Set-based Prototype and Metric Learning framework is proposed for image set classification.
• It can represent gallery image set using fewer but more discriminative prototypes.
• It is robust to the changes of feature length.
• It works better with fewer prototypes.
• It works better with k-means initialization than the random initialization.
摘要
•A Set-based Prototype and Metric Learning framework is proposed for image set classification.•It can represent gallery image set using fewer but more discriminative prototypes.•It is robust to the changes of feature length.•It works better with fewer prototypes.•It works better with k-means initialization than the random initialization.
论文关键词：Image set classification,Metric learning,Prototype learning,Video face recognition
论文评审过程：Received 9 October 2015, Revised 19 April 2016, Accepted 10 June 2016, Available online 20 June 2016, Version of Record 20 February 2017.
论文官网地址：https://doi.org/10.1016/j.imavis.2016.06.005
