Presentation-level privacy protection techniques for automated face recognition - a survey
Presentation-level privacy protection techniques for automated face recognition - a survey
The use of Biometric Facial Recognition (FR) Systems have become increasingly widespread, especially since the advent of deep neural network-based architectures (DNNs). Although FR systems provide substantial benefits in terms of security and safety, the use of these systems also raises significant privacy concerns. This paper discusses recent advances in facial identity hiding techniques, focusing on privacy protection approaches that hide or protect facial biometric data before camera devices capture the data. Moreover, we also discuss the state-of-the-art methods used to evaluate such privacy protection techniques. The primary motivation of this survey is to assess the relative performance of facial privacy protection methods and identify open challenges and future work that needs to be considered in this research area.
General Computer Science, Theoretical Computer Science
Hasan, Md. Rezwan
81389485-48b9-443c-b126-6382a7abddd6
Guest, Richard M.
93533dbd-b101-491b-83cc-39ccfdc18165
Deravi, Farzin
15f7c2ec-bd1e-4819-9ca9-7e179385dfa7
13 July 2023
Hasan, Md. Rezwan
81389485-48b9-443c-b126-6382a7abddd6
Guest, Richard M.
93533dbd-b101-491b-83cc-39ccfdc18165
Deravi, Farzin
15f7c2ec-bd1e-4819-9ca9-7e179385dfa7
Hasan, Md. Rezwan, Guest, Richard M. and Deravi, Farzin
(2023)
Presentation-level privacy protection techniques for automated face recognition - a survey.
ACM Computing Surveys, 56 (13s), [286].
(doi:10.1145/3583135).
Abstract
The use of Biometric Facial Recognition (FR) Systems have become increasingly widespread, especially since the advent of deep neural network-based architectures (DNNs). Although FR systems provide substantial benefits in terms of security and safety, the use of these systems also raises significant privacy concerns. This paper discusses recent advances in facial identity hiding techniques, focusing on privacy protection approaches that hide or protect facial biometric data before camera devices capture the data. Moreover, we also discuss the state-of-the-art methods used to evaluate such privacy protection techniques. The primary motivation of this survey is to assess the relative performance of facial privacy protection methods and identify open challenges and future work that needs to be considered in this research area.
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Accepted/In Press date: 30 January 2023
e-pub ahead of print date: 9 February 2023
Published date: 13 July 2023
Keywords:
General Computer Science, Theoretical Computer Science
Identifiers
Local EPrints ID: 489468
URI: http://eprints.soton.ac.uk/id/eprint/489468
ISSN: 0360-0300
PURE UUID: 9bf92d43-ff61-4dc3-b45f-fb81baba1bad
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Date deposited: 25 Apr 2024 16:30
Last modified: 28 Apr 2024 02:05
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Contributors
Author:
Md. Rezwan Hasan
Author:
Richard M. Guest
Author:
Farzin Deravi
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