Gait-ID on the move: Pace independent human identification using cell phone accelerometer dynamics

In this paper, we have proposed a robust, acceleration based, pace independent gait recognition framework using Android smartphones. From our extensive experiments using cyclostationarity and continuous wavelet transform spectrogram analysis on our gait acceleration database with both normal and fas...

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Bibliographic Details
Published in2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems pp. 8 - 15
Main Authors Juefei-Xu, F., Bhagavatula, C., Jaech, A., Prasad, U., Savvides, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2012
Subjects
Acceleration
Accelerometers
Biometrics (access control)
Covariance matrix
Legged locomotion
Sensors
Smart phones
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ISBN9781467313841
146731384X
DOI10.1109/BTAS.2012.6374552

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Summary:In this paper, we have proposed a robust, acceleration based, pace independent gait recognition framework using Android smartphones. From our extensive experiments using cyclostationarity and continuous wavelet transform spectrogram analysis on our gait acceleration database with both normal and fast paced data, our proposed algorithm has outperformed the state-of-the-art by a great margin. To be more specific, for normal to normal pace matching, we are able to achieve 99.4% verification rate (VR) at 0.1% false accept rate (FAR); for fast vs. fast, we are able to achieve 96.8% VR at 0.1% FAR; for the challenging normal vs. fast, we are still able to achieve 61.1% VR at 0.1% FAR. The findings have laid the foundation of pace independent gait recognition using mobile devices with high accuracy.
ISBN:9781467313841
146731384X
DOI:10.1109/BTAS.2012.6374552