Skip to main content
  • Conferences
  • Students
Sign in
  • Overview
  • Symposium Organizers
  • Registration Information
    • Registration Discounts
    • Venue, Hotel, and Travel
  • At a Glance
  • Calendar
  • Technical Sessions
  • Activities
    • Posters and Demos
    • Birds-of-a-Feather Sessions
  • Sponsorship
  • Students and Grants
    • Grants for Women
  • Services
  • Questions?
  • Help Promote!
  • For Participants
  • Call for Papers
  • Past Symposia
Gold Sponsor
Gold Sponsor
Silver Sponsor
Silver Sponsor
Bronze Sponsor
Bronze Sponsor
Bronze Sponsor
Bronze Sponsor
General Sponsor
General Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Media Sponsor
Industry Partner
Tweets by @usenix
  • Event Code of Conduct
  • Conference Network Policy
  • Statement on Environmental Responsibility Policy
Tweet

connect with us

Authors: 

Bryce Kellogg, Vamsi Talla, and Shyamnath Gollakota, University of Washington

Abstract: 

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.

Bryce Kellogg, University of Washington

Vamsi Talla, University of Washington

Shyamnath Gollakota, University of Washington

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {179757,
author = {Bryce Kellogg and Vamsi Talla and Shyamnath Gollakota},
title = {Bringing Gesture Recognition to All Devices},
booktitle = {11th USENIX Symposium on Networked Systems Design and Implementation (NSDI 14)},
year = {2014},
isbn = {978-1-931971-09-6},
address = {Seattle, WA},
pages = {303--316},
url = {https://www.usenix.org/conference/nsdi14/technical-sessions/presentation/kellogg},
publisher = {USENIX Association},
month = apr
}
Download
Kellogg PDF

Presentation Video 

Presentation Audio

MP3 Download

Download Audio

  • Log in or register to post comments
  • Privacy Policy
  • Contact Us

© USENIX
EIN 13-3055038