A framework of face synthesis based on multilinear analysis

Song Yuhao, Hui Zhang
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引用次数: 2

Abstract

This paper addresses the problem of privacy protection in face synthesis. We propose a new face synthesis approach based on tensor decomposition. By using the mathematical properties of tensor analysis, we decompose a face image into multiple factors so that the synthesis process could concentrate only on privacy related information. Then, we generate a new face image by altering the privacy related factors and keeping the other ones untouched. Compared to previous algorithms, our approach has the advantage in producing a synthetic face image without the risk of privacy leaking. We conduct the experiments in different datasets and factors to show the flexibility of the proposed approach. After gaining the synthesis images, we apply the automatic recognition algorithms for both expressions and faces to them. The experiment results demonstrate the effectiveness of our approach.
基于多线性分析的人脸综合框架
本文研究了人脸合成中的隐私保护问题。提出了一种新的基于张量分解的人脸合成方法。利用张量分析的数学性质,将人脸图像分解为多个因子,使合成过程只关注与隐私相关的信息。然后,我们通过改变隐私相关因素而保持其他因素不变来生成新的人脸图像。与以前的算法相比,我们的方法在生成合成人脸图像方面具有优势,并且没有隐私泄露的风险。我们在不同的数据集和因素中进行了实验,以显示所提出方法的灵活性。在获得合成图像后,我们将表情和人脸的自动识别算法应用于合成图像。实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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