论文标题
热到视觉面部识别的多项式评估
Multi-Metric Evaluation of Thermal-to-Visual Face Recognition
论文作者
论文摘要
在本文中，我们旨在使用机器学习来解决异质或跨光谱面部识别的问题，以从红外图像中综合视觉频谱面。视觉带脸部图像的合成允许更佳地提取面部特征，用于面部识别和/或验证。我们探索使用生成对抗网络（GAN）进行面部图像合成的能力，并使用预训练的卷积神经网络（CNN）检查这些图像的性能。使用CNN提取的功能用于面部识别和验证。当使用各种相似性度量进行面部验证时，我们会根据接受率探索性能。
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.
