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Paper Abstract and Keywords
Presentation 2024-02-29 15:00
Implementation and Evaluation of Privacy-Preserving Image Transformation Methods for Person Re-identification
Junpei Yamaguchi, Hajime Nada, Yumo Ouchi, Narishige Abe (Fujitsu) BioX2023-73 CNR2023-40
Abstract (in Japanese) (See Japanese page) 
(in English) Advances in machine learning have enabled high-accuracy tracking of individuals using surveillance cameras, making the development of privacy-preserving methods for such technology a critical issue. While image processing techniques such as blurring and pixelation have been proposed as privacy-preserving methods for person re-identification, these techniques have been found to create a trade-off between protection rate and re-identification accuracy. In this paper, we implement and evaluate two machine learning-based image processing methods that have achieved high protection rates and accuracy in privacy preservation for face and image recognition. Our results indicate that the first method, Learnable Privacy Budgets in Frequency Domain, provides a high protection rate, but it lacks accuracy and takes a long processing time. Additionally, our results show that the second method, Protective Perturbation, offers a high protection rate and accuracy, and possesses fast processing performance. However, there is a problem in that specific colors are hard to be process, resulting in the original colors being left intact.
Keyword (in Japanese) (See Japanese page) 
(in English) Person re-identification / privacy-preserving / image transformation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 394, BioX2023-73, pp. 18-23, Feb. 2024.
Paper # BioX2023-73 
Date of Issue 2024-02-22 (BioX, CNR) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF BioX2023-73 CNR2023-40

Conference Information
Committee CNR BioX  
Conference Date 2024-02-29 - 2024-03-01 
Place (in Japanese) (See Japanese page) 
Place (in English) NHK Science & Technology Research Laboratories 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To BioX 
Conference Code 2024-02-CNR-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Implementation and Evaluation of Privacy-Preserving Image Transformation Methods for Person Re-identification 
Sub Title (in English)  
Keyword(1) Person re-identification  
Keyword(2) privacy-preserving  
Keyword(3) image transformation  
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1st Author's Name Junpei Yamaguchi  
1st Author's Affiliation Fujitsu Limited (Fujitsu)
2nd Author's Name Hajime Nada  
2nd Author's Affiliation Fujitsu Limited (Fujitsu)
3rd Author's Name Yumo Ouchi  
3rd Author's Affiliation Fujitsu Limited (Fujitsu)
4th Author's Name Narishige Abe  
4th Author's Affiliation Fujitsu Limited (Fujitsu)
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Speaker Author-1 
Date Time 2024-02-29 15:00:00 
Presentation Time 30 minutes 
Registration for BioX 
Paper # BioX2023-73, CNR2023-40 
Volume (vol) vol.123 
Number (no) no.394(BioX), no.393(CNR) 
Page pp.18-23 
#Pages 6 
Date of Issue 2024-02-22 (BioX, CNR) 

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