Face recognition on large-scale video in the wild with hybrid Euclidean-and-Riemannian metric learning

作者：

Highlights：

• Represent image set by mean, covariance and Gaussian for discriminant information.

• Heterogeneous Euclidean and Riemannian kernels are exploited and fused clearly.

• Clear superiority over state-of-the-art set-based methods is achieved in testing.

摘要

Highlights•Represent image set by mean, covariance and Gaussian for discriminant information.•Heterogeneous Euclidean and Riemannian kernels are exploited and fused clearly.•Clear superiority over state-of-the-art set-based methods is achieved in testing.

论文关键词：Face recognition,Large-scale video,Multiple heterogeneous statistics,Hybrid Euclidean-and-Riemannian metric learning

论文评审过程：Received 1 October 2014, Revised 12 February 2015, Accepted 13 March 2015, Available online 20 March 2015, Version of Record 17 June 2015.

论文官网地址：https://doi.org/10.1016/j.patcog.2015.03.011