Towards robust gait recognition

Tenika Whytock; Alexander Belyaev; Neil Robertson

doi:10.1007/978-3-642-41939-3_51

Towards robust gait recognition

Tenika Whytock
, Alexander Belyaev
, Neil Robertson

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed)

5 Citations (Scopus)

Abstract

Covariate factors, such as persons carrying a bag and wearing a jacket, continue to cause significant misclassification in gait recognition. A novel and efficient approach learns a “typical” Gait Energy Image representation free from covariate factors which aids their mitigation in test and training data. Combating the influence of covariate factors yields a significant improvement of 11% over existing state of the art performance for sequences capturing persons wearing a jacket.

Original language	English
Title of host publication	Advances in Visual Computing
Subtitle of host publication	9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part II
Editors	George Bebis , Richard Boyle , Bahram Parvin, Darko Koracin, Baoxin Li, Fatih Porikli, Victor Zordan, James Klosowski , Sabine Coquillart , Xun Luo, Min Chen, David Gotz
Pages	523-531
Number of pages	9
ISBN (Electronic)	978-3-642-41939-3
DOIs	https://doi.org/10.1007/978-3-642-41939-3_51
Publication status	Published - 2013

Publication series

Name	Lecture Notes in Computer Science
Volume	8034
ISSN (Electronic)	0302-9743

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1007/978-3-642-41939-3_51

Cite this

Whytock, T., Belyaev, A., & Robertson, N. (2013). Towards robust gait recognition. In G. Bebis , R. Boyle , B. Parvin, D. Koracin, B. Li, F. Porikli, V. Zordan, J. Klosowski , S. Coquillart , X. Luo, M. Chen, & D. Gotz (Eds.), Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part II (pp. 523-531). (Lecture Notes in Computer Science; Vol. 8034). https://doi.org/10.1007/978-3-642-41939-3_51

Whytock, Tenika ; Belyaev, Alexander ; Robertson, Neil. / Towards robust gait recognition. Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part II. editor / George Bebis ; Richard Boyle ; Bahram Parvin ; Darko Koracin ; Baoxin Li ; Fatih Porikli ; Victor Zordan ; James Klosowski ; Sabine Coquillart ; Xun Luo ; Min Chen ; David Gotz . 2013. pp. 523-531 (Lecture Notes in Computer Science).

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abstract = "Covariate factors, such as persons carrying a bag and wearing a jacket, continue to cause significant misclassification in gait recognition. A novel and efficient approach learns a “typical” Gait Energy Image representation free from covariate factors which aids their mitigation in test and training data. Combating the influence of covariate factors yields a significant improvement of 11\% over existing state of the art performance for sequences capturing persons wearing a jacket.",

author = "Tenika Whytock and Alexander Belyaev and Neil Robertson",

year = "2013",

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Whytock, T, Belyaev, A & Robertson, N 2013, Towards robust gait recognition. in G Bebis , R Boyle , B Parvin, D Koracin, B Li, F Porikli, V Zordan, J Klosowski , S Coquillart , X Luo, M Chen & D Gotz (eds), Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part II. Lecture Notes in Computer Science, vol. 8034, pp. 523-531. https://doi.org/10.1007/978-3-642-41939-3_51

Towards robust gait recognition. / Whytock, Tenika; Belyaev, Alexander; Robertson, Neil.
Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part II. ed. / George Bebis ; Richard Boyle ; Bahram Parvin; Darko Koracin; Baoxin Li; Fatih Porikli; Victor Zordan; James Klosowski ; Sabine Coquillart ; Xun Luo; Min Chen; David Gotz . 2013. p. 523-531 (Lecture Notes in Computer Science; Vol. 8034).

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed)

TY - CHAP

T1 - Towards robust gait recognition

AU - Whytock, Tenika

AU - Belyaev, Alexander

AU - Robertson, Neil

PY - 2013

Y1 - 2013

N2 - Covariate factors, such as persons carrying a bag and wearing a jacket, continue to cause significant misclassification in gait recognition. A novel and efficient approach learns a “typical” Gait Energy Image representation free from covariate factors which aids their mitigation in test and training data. Combating the influence of covariate factors yields a significant improvement of 11% over existing state of the art performance for sequences capturing persons wearing a jacket.

AB - Covariate factors, such as persons carrying a bag and wearing a jacket, continue to cause significant misclassification in gait recognition. A novel and efficient approach learns a “typical” Gait Energy Image representation free from covariate factors which aids their mitigation in test and training data. Combating the influence of covariate factors yields a significant improvement of 11% over existing state of the art performance for sequences capturing persons wearing a jacket.

U2 - 10.1007/978-3-642-41939-3_51

DO - 10.1007/978-3-642-41939-3_51

M3 - Chapter (peer-reviewed)

SN - 978-3-642-41938-6

T3 - Lecture Notes in Computer Science

SP - 523

EP - 531

BT - Advances in Visual Computing

A2 - Bebis , George

A2 - Boyle , Richard

A2 - Parvin, Bahram

A2 - Koracin, Darko

A2 - Li, Baoxin

A2 - Porikli, Fatih

A2 - Zordan, Victor

A2 - Klosowski , James

A2 - Coquillart , Sabine

A2 - Luo, Xun

A2 - Chen, Min

A2 - Gotz , David

ER -

Whytock T, Belyaev A, Robertson N. Towards robust gait recognition. In Bebis G, Boyle R, Parvin B, Koracin D, Li B, Porikli F, Zordan V, Klosowski J, Coquillart S, Luo X, Chen M, Gotz D, editors, Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part II. 2013. p. 523-531. (Lecture Notes in Computer Science). doi: 10.1007/978-3-642-41939-3_51

Towards robust gait recognition

Abstract

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