Coupled discriminant mappings for heterogeneous face recognition

Xinli Cao; Ke Wen; Likun Huang; Bing Tang; Wei Zhang

doi:10.1117/12.2538163

14 February 2020 Coupled discriminant mappings for heterogeneous face recognition

Xinli Cao, Ke Wen, Likun Huang, Bing Tang, Wei Zhang

Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 114300P (2020) https://doi.org/10.1117/12.2538163
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

Previous efforts on heterogeneous face recognition typically assume each subject has multiple training samples. However, this assumption may not hold in some special cases such as law-enforcement where only a Single Sample Per Person (SSPP) exists in the training set. For face recognition in SSPP scenario, it often suffers from overfitting and singular matrix problems. To solve this problem, we propose a novel learning-based algorithm called Coupled Discriminant Mapping (CDM) for heterogeneous face recognition. The CDM method finds a common space and learns a couple of discriminant projections for two different modalities without depending on the intra-class scatters. In the common space ,images of the same person are pulled into close proximity even if they come through different modalities meanwhile all the image under the same modality are pushed apart since each image belongs to a distinct class. The performance of CDM method is evaluated in two tasks: visual face image vs. near infrared face image and conventional face recognition. Experiments are conducted on two widely studied databases to show the effectiveness and consistence of the proposed CDM method.

Citation Download Citation

Xinli Cao, Ke Wen, Likun Huang, Bing Tang, and Wei Zhang "Coupled discriminant mappings for heterogeneous face recognition", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114300P (14 February 2020); https://doi.org/10.1117/12.2538163

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KEYWORDS

Facial recognition systems

Code division multiplexing

Near infrared

Databases

Simulation of CCA and DLA aggregates

Feature extraction

Associative arrays

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