Using gait as a biometric, via phase-weighted magnitude spectra

Cunado, D., Nixon, M.S. and Carter, J.N. (1997) Using gait as a biometric, via phase-weighted magnitude spectra. Proceedings of 1st Int. Conf. on Audio- and Video-Based Biometric Person Authentication Springer Verlag, 95--102.


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Gait is a biometric which is subject to increasing interest. Current approaches include modelling gait as a spatio-temporal sequence and as an articulated model. By considering legs only, gait can be considered to be the motion of interlinked pendula. We describe how the Hough transform is used to extract the lines which represent legs in sequences of video images. The change in inclination of these lines follows simple harmonic motion; this motion is used as the gait biometric. The method of least squares is used to smooth the data and to infill for missing points. Then, Fourier transform analysis is used to reveal the frequency components of the change in inclination of the legs. The transform data is then classified using the k-nearest neighbour rule. Experimental analysis shows how phase-weighted Fourier magnitude spectra afford an improved classification rate over use of just magnitude spectra. Accordingly, it appears that it is not just the frequency content which makes gait a practical biometric, but its phase as well.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: Organisation: IAPR Address: Berlin
Divisions : Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Southampton Wireless Group
ePrint ID: 250040
Accepted Date and Publication Date:
March 1997Published
Date Deposited: 04 May 1999
Last Modified: 31 Mar 2016 13:50
Further Information:Google Scholar

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