Speed invariant gait recognition-The enhanced mutual subspace method.

This paper introduces an enhanced MSM (Mutual Subspace Method) methodology for gait recognition, to provide robustness to variations in walking speed. The enhanced MSM (eMSM) methodology expands and adapts the MSM, commonly used for face recognition, which is a static/physiological biometric, to gai...

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Autores principales:	Yumi Iwashita, Hitoshi Sakano, Ryo Kurazume, Adrian Stoica
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4819889a626b4bbbb3f45ac064eb392b
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id	oai:doaj.org-article:4819889a626b4bbbb3f45ac064eb392b
record_format	dspace
spelling	oai:doaj.org-article:4819889a626b4bbbb3f45ac064eb392b2021-12-02T20:18:21ZSpeed invariant gait recognition-The enhanced mutual subspace method.1932-620310.1371/journal.pone.0255927https://doaj.org/article/4819889a626b4bbbb3f45ac064eb392b2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0255927https://doaj.org/toc/1932-6203This paper introduces an enhanced MSM (Mutual Subspace Method) methodology for gait recognition, to provide robustness to variations in walking speed. The enhanced MSM (eMSM) methodology expands and adapts the MSM, commonly used for face recognition, which is a static/physiological biometric, to gait recognition, which is a dynamic/behavioral biometrics. To address the loss of accuracy during calculation of the covariance matrix in the PCA step of MSM, we use a 2D PCA-based mutual subspace. Furhtermore, to enhance the discrimination capability, we rotate images over a number of angles, which enables us to extract richer gait features to then be fused by a boosting method. The eMSM methodology is evaluated on existing data sets which provide variable walking speed, i.e. CASIA-C and OU-ISIR gait databases, and it is shown to outperform state-of-the art methods. While the enhancement to MSM discussed in this paper uses combinations of 2D-PCA, rotation, boosting, other combinations of operations may also be advantageous.Yumi IwashitaHitoshi SakanoRyo KurazumeAdrian StoicaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0255927 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yumi Iwashita Hitoshi Sakano Ryo Kurazume Adrian Stoica Speed invariant gait recognition-The enhanced mutual subspace method.
description	This paper introduces an enhanced MSM (Mutual Subspace Method) methodology for gait recognition, to provide robustness to variations in walking speed. The enhanced MSM (eMSM) methodology expands and adapts the MSM, commonly used for face recognition, which is a static/physiological biometric, to gait recognition, which is a dynamic/behavioral biometrics. To address the loss of accuracy during calculation of the covariance matrix in the PCA step of MSM, we use a 2D PCA-based mutual subspace. Furhtermore, to enhance the discrimination capability, we rotate images over a number of angles, which enables us to extract richer gait features to then be fused by a boosting method. The eMSM methodology is evaluated on existing data sets which provide variable walking speed, i.e. CASIA-C and OU-ISIR gait databases, and it is shown to outperform state-of-the art methods. While the enhancement to MSM discussed in this paper uses combinations of 2D-PCA, rotation, boosting, other combinations of operations may also be advantageous.
format	article
author	Yumi Iwashita Hitoshi Sakano Ryo Kurazume Adrian Stoica
author_facet	Yumi Iwashita Hitoshi Sakano Ryo Kurazume Adrian Stoica
author_sort	Yumi Iwashita
title	Speed invariant gait recognition-The enhanced mutual subspace method.
title_short	Speed invariant gait recognition-The enhanced mutual subspace method.
title_full	Speed invariant gait recognition-The enhanced mutual subspace method.
title_fullStr	Speed invariant gait recognition-The enhanced mutual subspace method.
title_full_unstemmed	Speed invariant gait recognition-The enhanced mutual subspace method.
title_sort	speed invariant gait recognition-the enhanced mutual subspace method.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/4819889a626b4bbbb3f45ac064eb392b
work_keys_str_mv	AT yumiiwashita speedinvariantgaitrecognitiontheenhancedmutualsubspacemethod AT hitoshisakano speedinvariantgaitrecognitiontheenhancedmutualsubspacemethod AT ryokurazume speedinvariantgaitrecognitiontheenhancedmutualsubspacemethod AT adrianstoica speedinvariantgaitrecognitiontheenhancedmutualsubspacemethod
_version_	1718374281004449792

Speed invariant gait recognition-The enhanced mutual subspace method.

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