论文标题
差分3D面部识别:将3D添加到您的最新2D方法
Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method
论文作者
论文摘要
主动照明是增强2D面部识别并使其更健壮的重要补充,例如欺骗攻击和弱光条件。在目前的工作中,我们表明,有可能采用主动照明以增强具有3D功能的最新2D面部识别方法,同时绕过3D重建的复杂任务。关键的想法是在测试上进行投影面对高空间频率模式,这使我们能够同时恢复真实的3D信息以及标准的2D面部图像。因此,可以透明地应用最新的2D面部识别解决方案,而从输入图像的高频组件中提取互补的3D面部特征。 ND-2006数据集的实验结果表明,提出的想法可以显着提高面部识别性能,并显着提高欺骗攻击的鲁棒性。
Active illumination is a prominent complement to enhance 2D face recognition and make it more robust, e.g., to spoofing attacks and low-light conditions. In the present work we show that it is possible to adopt active illumination to enhance state-of-the-art 2D face recognition approaches with 3D features, while bypassing the complicated task of 3D reconstruction. The key idea is to project over the test face a high spatial frequency pattern, which allows us to simultaneously recover real 3D information plus a standard 2D facial image. Therefore, state-of-the-art 2D face recognition solution can be transparently applied, while from the high frequency component of the input image, complementary 3D facial features are extracted. Experimental results on ND-2006 dataset show that the proposed ideas can significantly boost face recognition performance and dramatically improve the robustness to spoofing attacks.