Learning structured ordinal measures for video based face recognition

Ran He, Tieniu Tan, Larry S. Davis, Zhenan Sun

Abstract: 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.