Abstract
Today's geo-location estimation approaches are able to infer the location of a target image using its visual content alone. These approaches typically exploit visual matching techniques, applied to a large collection of background images with known geo-locations. Users who are unaware that visual analysis and retrieval approaches can compromise their geo-privacy, unwittingly open themselves to risks of crime or other unintended consequences. This paper lays the groundwork for a new approach to geo-privacy of social images: Instead of requiring a change of user behavior, we start by investigating users' existing photo-sharing practices. We carry out a series of experiments using a large collection of social images (8.5M) to systematically analyze how photo editing practices impact the performance of geo-location estimation. We find that standard image enhancements, including filters and cropping, already serve as natural geo-privacy protectors. In our experiments, up to 19% of images whose location would otherwise be automatically predictable were unlocalizeable after enhancement. We conclude that it would be wrong to assume that geo-visual privacy is a lost cause in today's world of rapidly maturing machine learning. Instead, protecting users against the unwanted effects of pixel-based inference is a viable research field. A starting point is understanding the geo-privacy bonus of already established user behavior.
Original language | English |
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Title of host publication | Proceedings of the 2017 ACM International Conference on Multimedia Retrieval |
Place of Publication | New York |
Publisher | Association for Computing Machinery (ACM) |
Pages | 84-92 |
Number of pages | 9 |
ISBN (Electronic) | 978-1-4503-4701-3 |
DOIs | |
Publication status | Published - 2017 |
Event | ICMR 2017: ACM International Conference on Multimedia Retrieval - Bucharest, Romania Duration: 6 Jun 2017 → 9 Jun 2017 http://www.icmr2017.ro/ |
Conference
Conference | ICMR 2017 |
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Country/Territory | Romania |
City | Bucharest |
Period | 6/06/17 → 9/06/17 |
Internet address |
Keywords
- geo-privacy
- geo-location estimation
- usable privacy for multimedia retrieval