Catch Smart Glasses If You Scan: Robot-Controlled vs. UI-Guided

As smart glasses become increasingly lightweight and suitable for all-day wearables, they show strong potential to serve as the next-generation mobile platforms that provide an AR interface bridging human experience and AI perception. However, a serious concern about its misuse has recently been reported [2] and has attracted public attention: smart glasses can be used as cheating tools in competitions and exams when they are indistinguishable from regular glasses. Our previous work [3] introduces a non-invasive smart glasses detection solution that leverages two unique AR optical signatures found in current smart glasses: eye glow (i.e., light leakage from AR waveguide displays) and rainbow pattern (i.e., diffraction of ambient light on AR waveguide displays). In this approach, glasses need to be scanned manually using the cameras on off-the-shelf smartphones. However, it is challenging to maintain comprehensive, multi-angle coverage that guarantees consistent and accurate detection performance, as their scanning trajectories may vary significantly and are unable to capture frames containing eye glow or rainbow patterns. Inspired by this, in this demo, we introduce two glasses scanning pipelines: (1) a robot arm-based, controllable smart glasses scanning platform; and (2) a UI-guided smart glasses scanning solution.