Learning structured ordinal measures for video based face recognition

作者：

Highlights：

• We proposed a structural ordinal measure (SOM) method by using output structures.

• SOM encourages ordinal features from the same class to have similar binary codes.

• We propose a self-correcting method to discretely binarize image-set samples.

• SOM achieved state-of-the-art results on several datasets.

摘要

•We proposed a structural ordinal measure (SOM) method by using output structures.•SOM encourages ordinal features from the same class to have similar binary codes.•We propose a self-correcting method to discretely binarize image-set samples.•SOM achieved state-of-the-art results on several datasets.

论文关键词：Ordinal measure,Metric learning,Local feature

论文评审过程：Received 24 August 2016, Revised 13 December 2016, Accepted 2 February 2017, Available online 3 February 2017, Version of Record 21 November 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.02.005