Privacy-friendly photo capturing and sharing system

Abstract

The wide adoption of smart devices with onboard cameras facilitates photo capturing and sharing, but greatly increases people's concern on privacy infringement. Here we seek a solution to respect the privacy of persons being photographed in a smarter way that they can be automatically erased from photos captured by smart devices according to their requirements. To make this work, we need to address three challenges: 1) how to enable users explicitly express their privacy protection intentions without wearing any visible specialized tag, and 2) how to associate the intentions with persons in captured photos accurately and efficiently. Furthermore, 3) the association process itself should not cause portrait information leakage and should be accomplished in a privacy-preserving way. In this work, we design, develop, and evaluate a system, called COIN (Cloak Of INvisibility), that enables a user to flexibly express her privacy requirement and empowers the photo service provider (or image taker) to exert the privacy protection policy. Leveraging the visual distinguishability of people in the field-of-view and the dimension-order-independent property of vector similarity measurement, COIN achieves high accuracy and low overhead. We implement a prototype system, and our evaluation results on both the trace-driven and real-life experiments confirm the feasibility and efficiency of our system.