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2019 | OriginalPaper | Chapter

Multi-layer Perceptron Architecture for Kinect-Based Gait Recognition

Authors : A. S. M. Hossain Bari, Marina L. Gavrilova

Published in: Advances in Computer Graphics

Publisher: Springer International Publishing

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Abstract

Accurate gait recognition is of high significance for numerous industrial and consumer applications, including virtual reality, online games, medical rehabilitation, video surveillance, and others. This paper proposes multi-layer perceptron (MLP) based neural network architecture for human gait recognition. Two unique geometric features: joint relative cosine dissimilarity (JRCD) and joint relative triangle area (JRTA) are introduced. These features are view and pose invariant, and thus enhance recognition performance. MLP model is trained using dynamic JRTA and JRCD sequences. The performance of the proposed MLP architecture is evaluated on publicly available 3D Kinect skeleton gait database and is shown to be superior to other state-of-the-art methods.

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Literature
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Metadata
Title
Multi-layer Perceptron Architecture for Kinect-Based Gait Recognition
Authors
A. S. M. Hossain Bari
Marina L. Gavrilova
Copyright Year
2019
Book
Advances in Computer Graphics

Print ISBN: 978-3-030-22513-1

Electronic ISBN: 978-3-030-22514-8

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-22514-8_31

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