Frogeye: Perception of the slightest tag motion

Lei Yang, Yong Qi, Jianbing Fang, Xuan Ding, Tianci Liu, Mo Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

26 Citations (Scopus)

Abstract

Existing methods in RFID systems often employ presence or absence fashion to detect the tags' motions, so they cannot meet motion detection requirement in many applications. Our recent observations suggest that the signal strength backscat-tered from the tag is hypersensitive to its position, inspiring us to perceive the tag motion through its radio signal strength changes. Motion perception is not trivial and challenged by weak stability of strength in that any other interference or noise may incur significant changes as well, resulting in high false positives. To tackle this issue, we propose to model the strength via the Mixture of Gaussian Model (MoG). The problem is thus converted to foreground segment in computer vision with the help of Strength Image, where the technique of MoG based background subtraction is employed. We then implement a prototype using commercial off-the-shelf products. The evaluation results show that the slightest tag motion (∼ 10cm) can be precisely perceived, and the accuracy is up to 92.34% while the false positive is suppressed under 0.5%.
Original languageEnglish
Title of host publicationIEEE INFOCOM 2014 - IEEE Conference on Computer Communications
PublisherIEEE
Pages2670-2678
Number of pages9
ISBN (Print)9781479933600
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014 - Toronto, ON, Canada
Duration: 27 Apr 20142 May 2014

Conference

Conference33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
CountryCanada
CityToronto, ON
Period27/04/142/05/14

Keywords

  • Background substruction
  • Mixture of Gaussian Model
  • Motion detection
  • RFID

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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