Bringing gesture recognition to all devices 论文

摘要

Existing gesture-recognition systems consume signifi-cant power and computational resources that limit how they may be used in low-end devices. We introduce AllSee, the first gesture-recognition system that can op-erate on a range of computing devices including those with no batteries. AllSee consumes three to four or-ders of magnitude lower power than state-of-the-art sys-tems and can enable always-on gesture recognition for smartphones and tablets. It extracts gesture information from existing wireless signals (e.g., TV transmissions), but does not incur the power and computational over-heads of prior wireless approaches. We build AllSee prototypes that can recognize gestures on RFID tags and power-harvesting sensors. We also integrate our hard-ware with an off-the-shelf Nexus S phone and demon-strate gesture recognition in through-the-pocket scenar-ios. Our results show that AllSee achieves classification accuracies as high as 97 % over a set of eight gestures. 1