从单个二维图像重建三维人脸用于人脸识别

Yuankui Hu, Ying Zheng, Zengfu Wang
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引用次数: 17

摘要

本文提出了一种基于合成样例的人脸识别框架,用于不同姿态和光照条件下的人脸识别。我们的目的是构建一个人脸识别系统,仅根据每个人的单一正面人脸图像进行识别。该框架由三个主要部分组成。首先,介绍了一种基于变形的三维人脸建模技术,该技术可以从具有通用三维人脸模型的人的单个正面人脸图像中创建单个三维人脸模型。然后,对不同光照和视角下的虚拟人脸进行合成。最后,以合成的虚拟人脸作为训练样本,构造了基于特征人脸的分类器。实验结果表明,所提出的三维人脸建模技术是有效的,合成的人脸样本可以显著提高不同姿态和光照条件下的人脸识别精度。
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Reconstruction of 3D Face from a Single 2D Image for Face Recognition
In this paper, a synthetic exemplar based framework for face recognition with variant pose and illumination is proposed. Our purpose is to construct a face recognition system only according to one single frontal face image of each person for recognition. The framework consists of three main parts. First, a deformation based 3D face modeling technique is introduced to create an individual 3D face model from a single frontal face image of a person with a generic 3D face model. Then, the virtual faces for recognition at various lightings and views are synthesized. Finally, an Eigenfaces based classifier is constructed where the virtual faces synthesized are used as training exemplars. The experimental results show that the proposed 3D face modeling technique is efficient and the synthetic face exemplars can significantly improve the accuracy of face recognition with variant pose and illumination.
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