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Model-Based Illumination Correction for Face Images in Uncontrolled Scenarios

机译:在不受控制的场景中基于模型的面部图像照明校正

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Face Recognition under uncontrolled illumination conditions is partly an unsolved problem. Several illumination correction methods have been proposed, but these are usually tested on illumination conditions created in a laboratory. Our focus is more on uncontrolled conditions. We use the Phong model which allows us to model ambient light in shadow areas. By estimating the face surface and illumination conditions, we are able to reconstruct a face image containing frontal illumination. The reconstructed face images give a large improvement in performance of face recognition in uncontrolled conditions.
机译:在不受控制的照明条件下的人脸识别部分尚未解决。已经提出了几种照明校正方法,但是这些方法通常是在实验室创建的照明条件下进行测试的。我们的重点更多地放在不受控制的条件上。我们使用Phong模型,该模型允许我们对阴影区域中的环境光进行建模。通过估计面部表面和照明条件,我们能够重建包含正面照明的面部图像。重建的面部图像在不受控制的条件下大大改善了面部识别性能。

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