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2016 | OriginalPaper | Chapter

Multi-Kernel Fuzzy-Based Local Gabor Patterns for Gait Recognition

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

Published in: Advances in Visual Computing

Publisher: Springer International Publishing

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Abstract

This paper proposes a novel multi-kernel fuzzy-based local Gabor binary patterns method (MFLGBP) for the purpose of gait representation and recognition. First, we construct the gait energy image (GEI) from mean motion cycle of a gait sequence. Then, we apply Gabor filters and encode the variations in the Gabor magnitude by using a kernel-based fuzzy local binary pattern (KFLBP) operator. Finally, classification is performed using a support vector machine (SVM). Experiments are carried out using the benchmark CASIA B gait database. Our proposed feature extraction method has shown promising performance in terms of correct recognition rate as compared to other methods.

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Metadata
Title
Multi-Kernel Fuzzy-Based Local Gabor Patterns for Gait Recognition
Authors
Amer G. Binsaadoon
El-Sayed M. El-Alfy
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-50835-1_71

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