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Facial Feature Extraction and Change Analysis Using Photometric Stereo

机译:使用光度立体的面部特征提取和变化分析

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This paper presents a new technique for three-dimensional face analysis aimed towards improving the robustness of face recognition. All of the 3D data used in the paper are obtained from a high-speed photometric stereo arrangement. First, a nose detection algorithm is presented, which is largely based on existing work, before a novel method for finding the nasion is described. Both of these methods rely solely on the 3D data. A new eye detection method is then described that uses a combination of 3D and 2D information with adaptive thresholding applied to the region of the image surrounding the eyes. The next main contribution of the paper is an analysis of the effects of makeup and facial hair on the success of the reconstruction and feature detection. We found that our method is very robust to such complications and can also handle spectacles and pose variation in many cases.
机译:本文提出了一种新的三维人脸分析技术,旨在提高人脸识别的鲁棒性。本文中使用的所有3D数据均来自高速光度立体布置。首先,介绍了一种基于现有工作的鼻子检测算法,然后介绍了一种找到鼻孔的新颖方法。这两种方法仅依赖于3D数据。然后描述了一种新的眼睛检测方法,该方法使用3D和2D信息的组合,并且将自适应阈值应用于眼睛周围图像的区域。本文的下一个主要贡献是分析化妆和面部毛发对重建和特征检测成功的影响。我们发现我们的方法对于这种并发症非常健壮,并且在许多情况下还可以处理眼镜和姿势变化。

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