Volumetric video (VV) offers photorealistic 3D capture for immersive educational VR, often created by instructors through live-streamed lessons or prerecorded demonstrations. While enhancing engagement and presence, such instructor-produced content can unintentionally expose sensitive objects, personal information, or biometric identifiers, and may intensify feelings of surveillance. This poster examines these privacy risks in using VV for educational VR and presents a research agenda focused on integrating diminished reality (DR) techniques and real-time 3D scene understanding into VV pipelines to dynamically sanitize environments while balancing realism and privacy.
Abstract
Summary
When teachers record lifelike 3D videos for VR classrooms, they can accidentally reveal private details like personal belongings or biometric data. This work maps out those privacy risks and proposes a roadmap for automatically removing sensitive information from 3D educational content while keeping the experience realistic and engaging.