| Title |
A Face Privacy Protection Scheme Using Cnn Based Roi Editing |
| ID_Doc |
1618 |
| Authors |
Peng F.; Ping G.-L.; Ge S.-K. |
| Year |
2019 |
| Published |
Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 |
| DOI |
http://dx.doi.org/10.1109/HPCC/SmartCity/DSS.2019.00060 |
| Abstract |
Aiming at the deficiencies of the current face privacy protection based on image editing in terms of protection capability and image utility, a novel face privacy protection scheme using CNN based ROI (Region of interest) editing is proposed. In this paper, a novel face ROI calculation method based on CNN (convolutional neural Network) is first put forward. A set of CNN networks is selected and utilized to calculate the gradient of each face image in an image dataset, and then an average gradient image is obtained from the image gradients. After that, the sub-ROIs are determined from the average gradient image, and different sub-ROIs have different contribution to the output of the CNN. Based on face ROI editing, a privacy protection scheme is put forward, which is adaptive to the existing privacy protection methods such as blurring, pixelization, encryption and etc. Experimental results and analysis show that it can achieve the same privacy protection capability with less modification and better image quality compared with the existing methods. © 2019 IEEE. |
| Author Keywords |
convolutional neural network; face image; privacy protection; region of Interest |
