Static Hand Gesture Recognition Based on Convolutional Neural Networks

This paper proposes a gesture recognition method using convolutional neural networks. The procedure involves the application of morphological filters, contour generation, polygonal approximation, and segmentation during preprocessing, in which they contribute to a better feature extraction. Training...

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Main Authors: Raimundo F. Pinto, Carlos D. B. Borges, Antônio M. A. Almeida, Iális C. Paula
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2019/4167890
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author Raimundo F. Pinto
Carlos D. B. Borges
Antônio M. A. Almeida
Iális C. Paula
author_facet Raimundo F. Pinto
Carlos D. B. Borges
Antônio M. A. Almeida
Iális C. Paula
author_sort Raimundo F. Pinto
collection DOAJ
description This paper proposes a gesture recognition method using convolutional neural networks. The procedure involves the application of morphological filters, contour generation, polygonal approximation, and segmentation during preprocessing, in which they contribute to a better feature extraction. Training and testing are performed with different convolutional neural networks, compared with architectures known in the literature and with other known methodologies. All calculated metrics and convergence graphs obtained during training are analyzed and discussed to validate the robustness of the proposed method.
format Article
id doaj-art-2e20218c1ac749f8ad4fb5bea611e21e
institution Kabale University
issn 2090-0147
2090-0155
language English
publishDate 2019-01-01
publisher Wiley
record_format Article
series Journal of Electrical and Computer Engineering
spelling doaj-art-2e20218c1ac749f8ad4fb5bea611e21e2025-02-03T06:05:37ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552019-01-01201910.1155/2019/41678904167890Static Hand Gesture Recognition Based on Convolutional Neural NetworksRaimundo F. Pinto0Carlos D. B. Borges1Antônio M. A. Almeida2Iális C. Paula3Universidade Federal do Ceará, Sobral, Ceará 62010-560, BrazilUniversidade Federal do Ceará, Sobral, Ceará 62010-560, BrazilUniversidade Federal do Ceará, Sobral, Ceará 62010-560, BrazilUniversidade Federal do Ceará, Sobral, Ceará 62010-560, BrazilThis paper proposes a gesture recognition method using convolutional neural networks. The procedure involves the application of morphological filters, contour generation, polygonal approximation, and segmentation during preprocessing, in which they contribute to a better feature extraction. Training and testing are performed with different convolutional neural networks, compared with architectures known in the literature and with other known methodologies. All calculated metrics and convergence graphs obtained during training are analyzed and discussed to validate the robustness of the proposed method.http://dx.doi.org/10.1155/2019/4167890
spellingShingle Raimundo F. Pinto
Carlos D. B. Borges
Antônio M. A. Almeida
Iális C. Paula
Static Hand Gesture Recognition Based on Convolutional Neural Networks
Journal of Electrical and Computer Engineering
title Static Hand Gesture Recognition Based on Convolutional Neural Networks
title_full Static Hand Gesture Recognition Based on Convolutional Neural Networks
title_fullStr Static Hand Gesture Recognition Based on Convolutional Neural Networks
title_full_unstemmed Static Hand Gesture Recognition Based on Convolutional Neural Networks
title_short Static Hand Gesture Recognition Based on Convolutional Neural Networks
title_sort static hand gesture recognition based on convolutional neural networks
url http://dx.doi.org/10.1155/2019/4167890
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AT carlosdbborges statichandgesturerecognitionbasedonconvolutionalneuralnetworks
AT antoniomaalmeida statichandgesturerecognitionbasedonconvolutionalneuralnetworks
AT ialiscpaula statichandgesturerecognitionbasedonconvolutionalneuralnetworks