University of Oulu

Anran Xu, Zhongyi Zhou, Kakeru Miyazaki, Ryo Yoshikawa, Simo Hosio, and Koji Yatani. 2023. DIPA: An Image Dataset with Cross-cultural Privacy Concern Annotations. In 28th International Conference on Intelligent User Interfaces (IUI ’23 Companion), March 27–31, 2023, Sydney, NSW, Australia. ACM, New York, NY, USA, 8 pages.

DIPA : an image dataset with cross-cultural privacy concern annotations

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Author: Xu, Anran1; Zhou, Zhongyi1; Miyazaki, Kakeru1;
Organizations: 1Interactive Intelligent Systems Lab., The University of Tokyo Tokyo, Japan
2Center for Ubiquitous Computing, University of Oulu Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 5.9 MB)
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Language: English
Published: Association for Computing Machinery, 2023
Publish Date: 2023-05-08


Image privacy protection is an important topic in Human-Computer Interaction and usable security. Researchers have examined different aspects of image privacy by collecting samples by themselves. However, there does not exist a publicly-available dataset on image privacy, which prevents these efforts from sharing common technical foundations. We introduce DIPA, an open source dataset that provides content-level annotations that specifically focus on image privacy. We include 1,495 images from two existing datasets in DIPA, and augment them with 5,671 annotations. Each annotation includes reasons why the associated visual content can be privacy-threatening, a rating of how informative annotators thought the associated content is to threaten privacy, and another rating of how broadly the image could be shared. We also collected annotations from people living in Japan and UK to enable researchers and developers to perform analysis from the perspective of cultural differences. In this paper, we present the construction procedure of DIPA and report high-level statistics of the data we obtained. We hope that DIPA would accelerate various future research, including quantitative understandings of cultural differences on perceptions of image privacy and the development of robust recognition models for image privacy protection.

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ISBN: 979-8-4007-0107-8
Pages: 259 - 266
DOI: 10.1145/3581754.3584176
Host publication: IUI '23 Companion : Companion Proceedings of the 28th International Conference on Intelligent User Interfaces
Conference: International Conference on Intelligent User Interfaces
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Copyright information: © Owner/Author 2023. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in 28th International Conference on Intelligent User Interfaces (IUI ’23 Companion),