Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis
Nowadays, with smartphones, people can easily take photos, post photos to any social networks, and use the photos for various purposes. This leads to a social problem that unintended appearance in photos may threaten the facial privacy of photographed people. Some solutions to protect facial privacy...
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doaj-78731045e2ed4a9b8a86c39323da3c752020-11-25T01:19:49ZengMDPI AGInformation2078-24892020-10-011146846810.3390/info11100468Prevention of Unintended Appearance in Photos Based on Human Behavior AnalysisYuhi Kaihoko0Phan Xuan Tan1Eiji Kamioka2Graduate School of Engineering and Science, Shibaura Institute of Technology, Tokyo 135-8548, JapanDepartment of Information and Communications Engineering, Shibaura Institute of Technology, Tokyo 135-8548, JapanGraduate School of Engineering and Science, Shibaura Institute of Technology, Tokyo 135-8548, JapanNowadays, with smartphones, people can easily take photos, post photos to any social networks, and use the photos for various purposes. This leads to a social problem that unintended appearance in photos may threaten the facial privacy of photographed people. Some solutions to protect facial privacy in photos have already been proposed. However, most of them rely on different techniques to de-identify photos which can be done only by photographers, giving no choice to photographed person. To deal with that, we propose an approach that allows a photographed person to proactively detect whether someone is intentionally/unintentionally trying to take pictures of him. Thereby, he can have appropriate reaction to protect the facial privacy. In this approach, we assume that the photographed person uses a wearable camera to record the surrounding environment in real-time. The skeleton information of likely photographers who are captured in the monitoring video is then extracted and put into the calculation of dynamic programming score which is eventually compared with a threshold for recognition of photo-taking behavior. Experimental results demonstrate that by using the proposed approach, the photo-taking behavior is precisely recognized with high accuracy of 92.5%.https://www.mdpi.com/2078-2489/11/10/468photo-taking behaviorphoto capturing and sharingbystandershuman behavior analysisidentity protectionfacial privacy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuhi Kaihoko Phan Xuan Tan Eiji Kamioka |
spellingShingle |
Yuhi Kaihoko Phan Xuan Tan Eiji Kamioka Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis Information photo-taking behavior photo capturing and sharing bystanders human behavior analysis identity protection facial privacy |
author_facet |
Yuhi Kaihoko Phan Xuan Tan Eiji Kamioka |
author_sort |
Yuhi Kaihoko |
title |
Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis |
title_short |
Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis |
title_full |
Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis |
title_fullStr |
Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis |
title_full_unstemmed |
Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis |
title_sort |
prevention of unintended appearance in photos based on human behavior analysis |
publisher |
MDPI AG |
series |
Information |
issn |
2078-2489 |
publishDate |
2020-10-01 |
description |
Nowadays, with smartphones, people can easily take photos, post photos to any social networks, and use the photos for various purposes. This leads to a social problem that unintended appearance in photos may threaten the facial privacy of photographed people. Some solutions to protect facial privacy in photos have already been proposed. However, most of them rely on different techniques to de-identify photos which can be done only by photographers, giving no choice to photographed person. To deal with that, we propose an approach that allows a photographed person to proactively detect whether someone is intentionally/unintentionally trying to take pictures of him. Thereby, he can have appropriate reaction to protect the facial privacy. In this approach, we assume that the photographed person uses a wearable camera to record the surrounding environment in real-time. The skeleton information of likely photographers who are captured in the monitoring video is then extracted and put into the calculation of dynamic programming score which is eventually compared with a threshold for recognition of photo-taking behavior. Experimental results demonstrate that by using the proposed approach, the photo-taking behavior is precisely recognized with high accuracy of 92.5%. |
topic |
photo-taking behavior photo capturing and sharing bystanders human behavior analysis identity protection facial privacy |
url |
https://www.mdpi.com/2078-2489/11/10/468 |
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