Acoustic Gait Analysis using Support Vector Machines

Jasper Huang; Fabio Di Troia; Mark Stamp

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Paper

Acoustic Gait Analysis using Support Vector Machines

In Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ForSE, 545-552, 2018 , Funchal, Madeira, Portugal

Authors: Jasper Huang ; Fabio Di Troia and Mark Stamp

Affiliation: San Jose State University, United States

Keyword(s): Gait Recognition, Support Vector Machine, Acoustic Analysis, Biometric.

Abstract: Gait analysis, defined as the study of human locomotion, can provide valuable information for low-cost analytic and classification applications in security, medical diagnostics, and biomechanics. In comparison to visual-based gait analysis, audio-based gait analysis offers robustness to clothing variations, visibility issues, and angle complications. Current acoustic techniques rely on frequency-based features that are sensitive to changes in footwear and floor surfaces. In this research, we consider an approach to surface-independent acoustic gait analysis based on time differences between consecutive steps. We employ support vector machines (SVMs) for classification. Our approach achieves good classification rates with high discriminative one-vs-all capabilities and we believe that our technique provides a promising avenue for future development.

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Paper citation in several formats:

Huang, J.; Di Troia, F. and Stamp, M. (2018). Acoustic Gait Analysis using Support Vector Machines. In Proceedings of the 4th International Conference on Information Systems Security and Privacy - ForSE; ISBN 978-989-758-282-0; ISSN 2184-4356, SciTePress, pages 545-552. DOI: 10.5220/0006730705450552

@conference{forse18,
author={Jasper Huang. and Fabio {Di Troia}. and Mark Stamp.},
title={Acoustic Gait Analysis using Support Vector Machines},
booktitle={Proceedings of the 4th International Conference on Information Systems Security and Privacy - ForSE},
year={2018},
pages={545-552},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006730705450552},
isbn={978-989-758-282-0},
issn={2184-4356},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Information Systems Security and Privacy - ForSE
TI - Acoustic Gait Analysis using Support Vector Machines
SN - 978-989-758-282-0
IS - 2184-4356
AU - Huang, J.
AU - Di Troia, F.
AU - Stamp, M.
PY - 2018
SP - 545
EP - 552
DO - 10.5220/0006730705450552
PB - SciTePress