Built-in cameras on mobile and wearable devices enable a number of vision related applications, such as mobile augmented reality, continuous sensing, and life-logging systems. While wearable cameras with smaller size and higher resolution bring joy and convenience to human lives, being recorded by unreliable cameras has raised people's concerns about visual privacy, particularly the potential leak of identity. Consequently, protecting identity of people who are not willing to appear in the photo or video has become an urgent issue that has yet to be resolved. In this paper, we propose an interactive method for individuals to control their visual privacy based on privacy indicators and control rules. We design and implement a prototype on Android smartphones, which allows individuals to inform cameras of their privacy control intentions through interaction using tags, hand gestures, and their combinations. Protection measures such as blurring the face will be performed to remove individual's identifiable information according to control rules. Evaluation results of the overall performance and feedbacks from real users demonstrate the effectiveness and usability of our approach, showing potentials of interactive visual privacy control.
展开▼
