Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method

• URL: http://arxiv.org/abs/2004.03385v1
• Date: Fri, 3 Apr 2020 20:17:14 GMT
• Title: Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method
• Authors: J. Matias Di Martino, Fernando Suzacq, Mauricio Delbracio, Qiang Qiu, and Guillermo Sapiro
• Abstract summary: We show that it is possible to adopt active illumination to enhance state-of-the-art 2D face recognition approaches with 3D features. The proposed ideas can significantly boost face recognition performance and dramatically improve the robustness to spoofing attacks.
• Score: 90.26041504667451
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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