A Multi-Input Fusion Model for Privacy and Semantic Preservation in Facial Image Datasets
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Published:2023-06-02
Issue:11
Volume:13
Page:6799
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Yang Yuanzhe1, Niu Zhiyi2, Qiu Yuying3, Song Biao1, Zhang Xinchang1, Tian Yuan4
Affiliation:
1. School of Computer Science, Nanjing University of Information Science & Technology, Nanjing 210044, China 2. Institute of Electronic and Electrical Engineering, Civil Aviation Flight University of China, Deyang 618307, China 3. School of Data Science and Engineering, East China Normal University, Shanghai 200062, China 4. Nanjing Institute of Technology (NJIT), Nanjing 210094, China
Abstract
The widespread application of multimedia technologies such as video surveillance, online meetings, and drones facilitates the acquisition of a large amount of data that may contain facial features, posing significant concerns with regard to privacy. Protecting privacy while preserving the semantic contents of facial images is a challenging but crucial problem. Contemporary techniques for protecting the privacy of images lack the incorporation of the semantic attributes of faces and disregard the protection of dataset privacy. In this paper, we propose the Facial Privacy and Semantic Preservation (FPSP) model that utilizes similar facial feature replacement to achieve identity concealment, while adding semantic evaluation to the loss function to preserve semantic features. The proposed model is versatile and efficient in different task scenarios, preserving image utility while concealing privacy. Our experiments on the CelebA dataset demonstrate that the model achieves a semantic preservation rate of 77% while concealing the identities in facial images in the dataset.
Funder
National Key Research and Development Program of China National Science Foundation of China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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