In this paper, we propose a method for generating visually protected images, referred to as gradient-preserving images. The protected images allow us to directly extract Histogram-of-Oriented-Gradients (HOG) features for privacy-preserving machine learning. In an experiment, HOG features extracted from gradient-preserving images are applied to a face recognition algorithm to demonstrate the effectiveness of the proposed method.
翻译:在本文中,我们提出了一种生成视觉保护图像的方法,称为梯度保护图像。保护图像使我们能够直接提取方向梯度地图(HOG)特征,用于隐私保护机器学习。在一次实验中,从梯度保护图像中提取的HOG特征被用于面部识别算法,以证明拟议方法的有效性。