Next Article in Journal
Multiple Resolution Modeling: A Particular Case of Distributed Simulation
Previous Article in Journal
Design of Distributed Discrete-Event Simulation Systems Using Deep Belief Networks
Open AccessArticle

Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis

1
Graduate School of Engineering and Science, Shibaura Institute of Technology, Tokyo 135-8548, Japan
2
Department of Information and Communications Engineering, Shibaura Institute of Technology, Tokyo 135-8548, Japan
*
Authors to whom correspondence should be addressed.
Information 2020, 11(10), 468; https://doi.org/10.3390/info11100468
Received: 23 July 2020 / Revised: 28 September 2020 / Accepted: 29 September 2020 / Published: 2 October 2020
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%. View Full-Text
Keywords: photo-taking behavior; photo capturing and sharing; bystanders; human behavior analysis; identity protection; facial privacy photo-taking behavior; photo capturing and sharing; bystanders; human behavior analysis; identity protection; facial privacy
Show Figures

Figure 1

MDPI and ACS Style

Kaihoko, Y.; Tan, P.X.; Kamioka, E. Prevention of Unintended Appearance in Photos Based on Human Behavior Analysis. Information 2020, 11, 468.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop