A Gabor-based network for heterogeneous face recognition

作者：Oh Beom Seok; Oh Kangrok; Teoh Andrew Beng Jin; Lin Zhiping; Toh Kar Ann

来源：Neurocomputing, 2017, 261: 253-265.

DOI：10.1016/j.neucom.2015.11.137

• Heterogeneous face recognition
• Gabor features
• Extreme learning machine
• Random weighting

In this paper, we propose a single hidden-layer Gabor-based network for heterogeneous face recognition. The proposed input layer contains novel computational units which propagate geometrically localized input image sub-blocks to hidden nodes. The propagated pixels are then convolved with a set of Gabor kernels followed by a randomly weighted summation and a non-linear activation function operation. The output layer adopts a linear weighting scheme which can be deterministically estimated similar to that in extreme learning machine. Our experiments on three experimental scenarios using BERC visual-thermal infrared database and CASIA visual-near infrared database show promising results for the proposed network.

• 出版日期2017-10-25
• 单位南阳理工学院