Paper Info
Title
Privacy Protection Performance Of De-Identified Face Images With And Without Background
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.
Year
Venue
Keywords
2016
2016 39TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO)
face de-identification, privacy protection, face re-identification, seamless cloning
Field
DocType
Citations 
Facial recognition system,Computer vision,Three-dimensional face recognition,Pattern recognition,FERET,Computer science,Active appearance model,Artificial intelligence,Face detection,Information privacy,Principal component analysis
Conference
2
PageRank 
References 
Authors
0.36
15
5
Name
Order
Citations
PageRank
Zongji Sun1171.77
Li Meng2273.48
Aladdin M. Ariyaeeinia310412.00
Duan Xiaodong48516.18
Zheng-Hua Tan545760.32