Evaluating the Impact of Face Anonymization Methods on Computer Vision Tasks: A Trade-Off Between Privacy and Utility

Evaluating the Impact of Face Anonymization Methods on Computer Vision Tasks: A Trade-Off Between Privacy and Utility

Data anonymization is an essential prerequisite that enables data sharing in a privacy-preserving manner. However, anonymization affects the quality of the data and thus might affect the performance of later conducted data analysis. In this work, we investigate the influence of different image-based...

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Bibliographic Details
Main Authors: Roland Stenger, Steffen Busse, Jonas Sander, Thomas Eisenbarth, Sebastian Fudickar
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Image analysis
data privacy
synthetic data
computer vision
performance evaluation
face recognition
Online Access:https://ieeexplore.ieee.org/document/10804775/
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https://ieeexplore.ieee.org/document/10804775/

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