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Cameras are now pervasive on consumer devices, including smartphones, laptops, tablets, and new wearable devices like Google Glass and the Narrative Clip lifelogging camera. The ubiquity of these cameras will soon create a new era of visual sensing applications, for example, devices that collect photos and videos of our daily lives, augmented reality applications that help us understand and navigate the world around us, and community-oriented applications, e.g., where cameras close to a crisis tasked with obtaining a real-time "million-eye view" of the scene to guide first responders in an emergency. These technologies raise significant implications for individuals and society, including both potential benefits for individuals and communities, but also significant hazards including privacy invasion for individuals, and, if unchecked, for society, as surveillance causes a chilling effect in the public square. This research couples a sociological understanding of privacy with an investigation of technical mechanisms to address these needs. Issues such as context (e.g., capturing images for public use may be okay at a public event, but not in the home) and content (are individuals recognizable?) will be explored both on technical and sociological fronts: What can we determine about images, what does this mean in terms of privacy risk, and how can systems protect against risk to privacy?
Specific research challenges to be addressed include formulating technical means through image and context analysis to improve the privacy of people captured in images; exploring the unique privacy needs of camera owners and how image and contextual analysis can improve privacy; and developing image transformations to afford privacy as well as enable novel applications using the cloud and crowdsourcing. Companion sociological studies will examine how context affects privacy perceptions, the impact on perception of new technologies, and image-sharing behavior. These studies will guide each other, ensuring that mechanisms for image transformation/privatization, non-visual transformations (e.g., altering or obscuring image metadata) and other techniques can improve both privacy protection against automated analysis and how they affect individual perceptions of the invasiveness of the technology. Through a deeper understanding of the privacy implications of such technologies from both a social and technical perspective, the proposed research has the potential for profound and positive societal impact by laying a foundation for privacy-sensitive visual sensing techniques for a society where cameras are ubiquitous.
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TWC SBE: Medium: Collaborative: A Socio-Technical Approach to Privacy in a Camera-Rich World