Gait-based recognition for human identification using fuzzy local binary patterns

Amer G. Binsaadoon; El Sayed M. El-Alfy

doi:10.5220/0005693103140321

Gait-based recognition for human identification using fuzzy local binary patterns

Amer G. Binsaadoon, El Sayed M. El-Alfy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Scopus citations

Abstract

With the increasing security breaches nowadays, automated gait recognition has recently received increasing importance in video surveillance technology. In this paper, we propose a method for human identification at distance based on Fuzzy Local Binary Pattern (FLBP). After the Gait Energy Image (GEI) is generated as a spatiotemporal summary of a gait video sequence, a multi-region partitioning is applied and FLBP based features are extracted for each region. We also evaluate the performance under the variation of some factors including viewing angle, clothing and carrying conditions. The experimental work showed that GEI-FLBP with partitioning has remarkably enhanced the identification accuracy.

Original language	English
Title of host publication	ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence
Editors	Jaap van den Herik, Joaquim Filipe, Joaquim Filipe
Publisher	SciTePress
Pages	314-321
Number of pages	8
ISBN (Electronic)	9789897581724
DOIs	https://doi.org/10.5220/0005693103140321
State	Published - 2016

Publication series

Name	ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence
Volume	2

Bibliographical note

Publisher Copyright:
Copyright © 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

Keywords

Biometric
Fuzzy logic
Gait recognition
Human identification
Local Binary Pattern

ASJC Scopus subject areas

Software
Artificial Intelligence
Control and Systems Engineering

Access to Document

10.5220/0005693103140321

Cite this

Binsaadoon, A. G., & El-Alfy, E. S. M. (2016). Gait-based recognition for human identification using fuzzy local binary patterns. In J. van den Herik, J. Filipe, & J. Filipe (Eds.), ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence (pp. 314-321). (ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence; Vol. 2). SciTePress. https://doi.org/10.5220/0005693103140321

Binsaadoon, Amer G. ; El-Alfy, El Sayed M. / Gait-based recognition for human identification using fuzzy local binary patterns. ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence. editor / Jaap van den Herik ; Joaquim Filipe ; Joaquim Filipe. SciTePress, 2016. pp. 314-321 (ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence).

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abstract = "With the increasing security breaches nowadays, automated gait recognition has recently received increasing importance in video surveillance technology. In this paper, we propose a method for human identification at distance based on Fuzzy Local Binary Pattern (FLBP). After the Gait Energy Image (GEI) is generated as a spatiotemporal summary of a gait video sequence, a multi-region partitioning is applied and FLBP based features are extracted for each region. We also evaluate the performance under the variation of some factors including viewing angle, clothing and carrying conditions. The experimental work showed that GEI-FLBP with partitioning has remarkably enhanced the identification accuracy.",

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Binsaadoon, AG & El-Alfy, ESM 2016, Gait-based recognition for human identification using fuzzy local binary patterns. in J van den Herik, J Filipe & J Filipe (eds), ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence. ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence, vol. 2, SciTePress, pp. 314-321. https://doi.org/10.5220/0005693103140321

Gait-based recognition for human identification using fuzzy local binary patterns. / Binsaadoon, Amer G.; El-Alfy, El Sayed M.
ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence. ed. / Jaap van den Herik; Joaquim Filipe; Joaquim Filipe. SciTePress, 2016. p. 314-321 (ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - With the increasing security breaches nowadays, automated gait recognition has recently received increasing importance in video surveillance technology. In this paper, we propose a method for human identification at distance based on Fuzzy Local Binary Pattern (FLBP). After the Gait Energy Image (GEI) is generated as a spatiotemporal summary of a gait video sequence, a multi-region partitioning is applied and FLBP based features are extracted for each region. We also evaluate the performance under the variation of some factors including viewing angle, clothing and carrying conditions. The experimental work showed that GEI-FLBP with partitioning has remarkably enhanced the identification accuracy.

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Binsaadoon AG, El-Alfy ESM. Gait-based recognition for human identification using fuzzy local binary patterns. In van den Herik J, Filipe J, Filipe J, editors, ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence. SciTePress. 2016. p. 314-321. (ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence). doi: 10.5220/0005693103140321

Gait-based recognition for human identification using fuzzy local binary patterns

Abstract

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Bibliographical note

Keywords

ASJC Scopus subject areas

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