An Analysis of Different Approaches to Gait Recognition Using Cell Phone Based Accelerometers

Muhammad Muaaz, Rene Mayrhofer

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

35 Citations (Scopus)

Abstract

Biometric gait authentication using Personal Mobile Device (PMD) based accelerometer sensors offers a user-friendly, unobtrusive, and periodic way of authenticating individuals on PMD. In this paper, we present a technique for gait cycle extraction by incorporating the Piecewise Linear Approximation (PLA) technique. We also present two new approaches to classify gait features extracted from the cycle-based segmentation by using Support Vector Machines (SVMs); a) pre-computed data matrix, b) pre-computed kernel matrix. In the first approach, we used Dynamic Time Warping (DTW) distance to compute data matrices, and in the later DTW is used for constructing an elastic similarity measure based kernel function called Gaussian Dynamic Time Warp (GDTW) kernel. Both approaches utilize the DTW similarity measure and can be used for classifying equal length gait cycles, as well as different length gait cycles. To evaluate our approaches we used normal walk biometric gait data of 51 participants. This gait data is collected by attaching a PMD to the belt around the waist, on the right-hand side of the hip. Results show that these new approaches need to be studied more, and potentially lead us to design more robust and reliable gait authentication systems using PMD based accelerometer sensor.
Original languageEnglish
Title of host publicationProceedings - 11th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2013
PublisherACM Press
Pages293-300
Number of pages8
ISBN (Print)978-1-4503-2106-8
DOIs
Publication statusPublished - 2013
Event11th International Conference on Advances in Mobile Computing and Multimedia (MoMM2013) - Vienna, Austria
Duration: 2 Dec 20134 Dec 2013
http://www.iiwas.org/conferences/momm2013/

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th International Conference on Advances in Mobile Computing and Multimedia (MoMM2013)
CountryAustria
CityVienna
Period02.12.201304.12.2013
Internet address

Keywords

  • Authentication
  • accelerometer
  • biometrics
  • gait recognition
  • machine learning

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