Multi-Metric Evaluation of Thermal-to-Visual Face Recognition

• URL: http://arxiv.org/abs/2007.11987v1
• Date: Wed, 22 Jul 2020 10:18:34 GMT
• Title: Multi-Metric Evaluation of Thermal-to-Visual Face Recognition
• Authors: Kenneth Lai and Svetlana N. Yanushkevich
• Abstract summary: We aim to address the problem of heterogeneous or cross-spectral face recognition using machine learning to synthesize visual spectrum face from infrared images. We explore the ability to use Geneversarative Adrial Networks (GANs) for face image synthesis, and examine the performance of these images using pre-trained Convolutional Neural Networks (CNNs) The features extracted using CNNs are applied in face identification and verification.
• Score: 3.0255457622022486
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we aim to address the problem of heterogeneous or cross-spectral face recognition using machine learning to synthesize visual spectrum face from infrared images. The synthesis of visual-band face images allows for more optimal extraction of facial features to be used for face identification and/or verification. We explore the ability to use Generative Adversarial Networks (GANs) for face image synthesis, and examine the performance of these images using pre-trained Convolutional Neural Networks (CNNs). The features extracted using CNNs are applied in face identification and verification. We explore the performance in terms of acceptance rate when using various similarity measures for face verification.

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