  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.
