Privacy Protection Performance of De-identified Face Images with and without Background
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Author
Sun, Zongji
Meng, Li
Ariyaeeinia, Aladdin
Duan, Xiaodong
Tan, Zheng-Hua
Attention
2299/20286
Abstract
This paper presents an approach to blending a de-identified face region with its original background, for the purpose of completing the process of face de-identification. The re-identification risk of the de-identified FERET face images has been evaluated for the k-Diff-furthest face de-identification method, using several face recognition benchmark methods including PCA, LBP, HOG and LPQ. The experimental results show that the k-Diff-furthest face de-identification delivers high privacy protection within the face region while blending the de-identified face region with its original background may significantly increases the re-identification risk, indicating that de-identification must also be applied to image areas beyond the face region.