Institute of Optoelectronics, Military University of Technology, 2 Gen. S. Kaliskiego St., 00-908 Warsaw, Poland.
Sensors (Basel). 2021 May 10;21(9):3301. doi: 10.3390/s21093301.
This paper reports on a new approach to face verification in long-wavelength infrared radiation. Two face images were combined into one double image, which was then used as an input for a classification based on neural networks. For testing, we exploited two external and one homemade thermal face databases acquired in various variants. The method is reported to achieve a true acceptance rate of about 83%. We proved that the proposed method outperforms other studied baseline methods by about 20 percentage points. We also analyzed the issue of extending the performance of algorithms. We believe that the proposed double image method can also be applied to other spectral ranges and modalities different than the face.
本文报告了一种在长波红外辐射中进行人脸识别的新方法。将两幅人脸图像组合成一幅双图像，然后将其用作基于神经网络的分类的输入。在测试中，我们利用了两个外部和一个自制的热人脸数据库，这些数据库是在各种变体下获取的。该方法的真接受率约为 83%。我们证明，所提出的方法比其他研究的基线方法的性能高出约 20 个百分点。我们还分析了扩展算法性能的问题。我们相信，所提出的双图像方法也可以应用于其他光谱范围和与面部不同的模态。
