Privacy Protection in Mobile Photography with Face Cloaking
Year: 2024
Type: article
Abstract: In a world of increasing connectivity, privacy is becoming ever-more difficult to maintain. People have little control over the capture of their image while in public and have even less control over the online sharing or posting of their image. This leaves many people vulnerable to being tracked or profiled via their image’s presence in other people’s photos. This thesis implements and evaluates an approach to privacy protection that involves the photographers protecting the privacy of bystanders. Because most photographs are now being taken by smartphones, a mobile application is decidedly the technology that would best achieve widespread adoption and reduce threats to privacy. The implemented application can efficiently identify and cloak bystanders’ face images so that face recognition software are unable to correctly identify nor profile these bystanders, and it can do so without affecting the human-perceived quality of the photographs.
Author: Heng, Rithyka
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7042641807