Bringing Gesture Recognition to All Devices

Existing gesture-recognition systems consume significant 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 operate on a range of computing devices including those with no batteries. AllSee consumes three to four orders of magnitude lower power than state-of-the-art systems 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 overheads of prior wireless approaches. We build AllSee prototypes that can recognize gestures on RFID tags and power-harvesting sensors. We also integrate our hardware with an off-the-shelf Nexus S phone and demonstrate gesture recognition in through-the-pocket scenarios. Our results show that AllSee achieves classification accuracies as high as 97% over a set of eight gestures.

[1]  Fadel Adib,et al.  See through walls with WiFi! , 2013, SIGCOMM.

[2]  Steve Lazar,et al.  A Passive UHF RFID Transponder for EPC Gen 2 with -14dBm Sensitivity in 0.13μm CMOS , 2007, 2007 IEEE International Solid-State Circuits Conference. Digest of Technical Papers.

[3]  Gregory D. Abowd,et al.  SNUPI: sensor nodes utilizing powerline infrastructure , 2010, UbiComp.

[4]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[5]  Anish Arora,et al.  Towards radar-enabled sensor networks , 2006, IPSN.

[6]  Stefan Mangold,et al.  RFID shakables: pairing radio-frequency identification tags with the help of gesture recognition , 2013, CoNEXT.

[7]  Graeme E. Smith,et al.  Through-the-Wall Sensing of Personnel Using Passive Bistatic WiFi Radar at Standoff Distances , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Joshua R. Smith,et al.  Experimental results with two wireless power transfer systems , 2009, 2009 IEEE Radio and Wireless Symposium.

[9]  Anish Arora,et al.  Integrating Micropower Radar and Motes , 2003 .

[10]  R. Engelbrecht,et al.  DIGEST of TECHNICAL PAPERS , 1959 .

[11]  Desney S. Tan,et al.  SoundWave: using the doppler effect to sense gestures , 2012, CHI.

[12]  Desney S. Tan,et al.  An ultra-low-power human body motion sensor using static electric field sensing , 2012, UbiComp.

[13]  Tyler S. Ralston,et al.  Real-time through-wall imaging using an ultrawideband multiple-input multiple-output (MIMO) phased array radar system , 2010, 2010 IEEE International Symposium on Phased Array Systems and Technology.

[14]  Shwetak N. Patel,et al.  Whole-home gesture recognition using wireless signals , 2013, MobiCom.

[15]  Desney S. Tan,et al.  Humantenna: using the body as an antenna for real-time whole-body interaction , 2012, CHI.

[16]  Alanson P. Sample,et al.  Design of an RFID-Based Battery-Free Programmable Sensing Platform , 2008, IEEE Transactions on Instrumentation and Measurement.

[17]  G. Charvat,et al.  A Through-Dielectric Radar Imaging System , 2010, IEEE Transactions on Antennas and Propagation.

[18]  David Wetherall,et al.  Ambient backscatter: wireless communication out of thin air , 2013, SIGCOMM.

[19]  Tadayoshi Kohno,et al.  RFIDs and secret handshakes: defending against ghost-and-leech attacks and unauthorized reads with context-aware communications , 2008, CCS.