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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...
The k-anonymity approach adopted by k-Same face de-identification methods enables these methods to serve their purpose of privacy protection. However, it also forces every k original faces to share the same de-identified face, making it impossible to track individuals in a k-Same de-identified video. To address this issue, this paper presents an approach to the creation of distinguishable de-identified...
The extensive use of video surveillance along with advances in face recognition has ignited concerns about the privacy of the people identifiable in recorded documents. Prior research into face de-identification algorithms has successfully proposed k-anonymity methods that guarantee to thwart face recognition software. However, there has been little investigation into the preservation of the data...
The rising concern for privacy protection and the associated legal and social responsibilities have led to extensive research into the field of face de-identification over the last decade. To date, the most successful algorithms developed for face de-identification are those based on the k-Same de-identification, which guarantee a recognition rate lower than 1/k. However, the current k-Same solutions...
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