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3D Assisted 2D Face Recognition: Methodology

机译:3D辅助2D面部识别:方法论

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摘要

We address the problem of pose and illumination invariance in face recognition and propose to use explicit 3D model and variants of existing algorithms for both pose [Fit01, MSCA04] and illumination normalization [ZS04] prior to applying 2D face recognition algorithm. However, contrary to prior work we will use person specific, rather than general 3D face models. The proposed solution is realistic as for many applications the additional cost of acquiring 3D face images during enrolment of the subjects is acceptable. 3D sensing is not required during normal operation of the face recognition system. The proposed methodology achieves illumination invariance by estimating the illumination sources using the 3D face model. By-product of this process is the recovery of the face skin albedo which can be used as a photometrically normalised face image. Standard face recognition techniques can then be applied to such illumination corrected images.
机译:我们在面部识别中解决了对姿势和照明不变性的问题,并建议在应用2D面识别算法之前使用用于姿势[FIT01,MSCA04]和照明归一化[ZS04]的现有算法的显式3D模型和变体。然而,与事先工作相反,我们将使用特定于某人的人而不是一般的3D面部模型。所提出的解决方案是真实的,因为许多应用程序是可以接受获取在受试者中的3D面部图像的额外成本。在面部识别系统的正常操作期间不需要3D感测。所提出的方法通过使用3D面部模型估计照明来源来实现照明不变性。该过程的副产物是恢复面部皮肤反照孔,其可以用作光学归一化的面部图像。然后可以将标准面部识别技术应用于这种照明校正的图像。

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