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Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2017,9,11]]},"abstract":"<jats:p>Free-hand gestural input is essential for emerging user interactions. We present Aili, a table lamp reconstructing a 3D hand skeleton in real time, requiring neither cameras nor on-body sensing devices. Aili consists of an LED panel in a lampshade and a few low-cost photodiodes embedded in the lamp base. To reconstruct a hand skeleton, Aili combines 2D binary blockage maps from vantage points of different photodiodes, which describe whether a hand blocks light rays from individual LEDs to all photodiodes. Empowering a table lamp with sensing capability, Aili can be seamlessly integrated into the existing environment. Relying on such low-level cues, Aili entails lightweight computation and is inherently privacy-preserving. We build and evaluate an Aili prototype. Results show that Aili\u2019s algorithm reconstructs a hand pose within 7.2 ms on average, with 10.2\u00b0 mean angular deviation and 2.5-mm mean translation deviation in comparison to Leap Motion. We also conduct user studies to examine the privacy issues of Leap Motion and solicit feedback on Aili\u2019s privacy protection. 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