Gait-based Recognition for Human Identification using Fuzzy Local Binary Patterns

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

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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Paper Citation


in Harvard Style

Binsaadoon A. and El-Alfy E. (2016). Gait-based Recognition for Human Identification using Fuzzy Local Binary Patterns . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-172-4, pages 314-321. DOI: 10.5220/0005693103140321


in Bibtex Style

@conference{icaart16,
author={Amer G. Binsaadoon and El-Sayed M. El-Alfy},
title={Gait-based Recognition for Human Identification using Fuzzy Local Binary Patterns},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2016},
pages={314-321},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005693103140321},
isbn={978-989-758-172-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Gait-based Recognition for Human Identification using Fuzzy Local Binary Patterns
SN - 978-989-758-172-4
AU - Binsaadoon A.
AU - El-Alfy E.
PY - 2016
SP - 314
EP - 321
DO - 10.5220/0005693103140321