On the use of the quaternion generalized Gaussian distribution for footstep detection

Divya Venkatraman, Vinod V. Reddy, Andy W.H. Khong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

We propose a method to detect human footsteps from a vector-quaternion signal acquired by a tri-axial geophone. The quaternion generalized Gaussian distribution (QGGD) is derived to parameterize variations in the vector-quaternion signal using a shape parameter, quantifying non-Gaussianity and quaternion augmented covariance matrix, quantifying inter-channel correlation. The detection of footsteps is then formulated as binary hypotheses tests in terms of the parameters of the QGGD. The effectiveness of the proposed metrics is evaluated on recorded seismic data.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages6521-6525
Number of pages5
DOIs
Publication statusPublished - Oct 18 2013
Externally publishedYes
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period5/26/135/31/13

ASJC Scopus Subject Areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • footstep detection
  • quaternion
  • vector-sensor

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