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: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/4167890 |
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| _version_ | 1832550822709297152 |
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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 |
| work_keys_str_mv | AT raimundofpinto statichandgesturerecognitionbasedonconvolutionalneuralnetworks AT carlosdbborges statichandgesturerecognitionbasedonconvolutionalneuralnetworks AT antoniomaalmeida statichandgesturerecognitionbasedonconvolutionalneuralnetworks AT ialiscpaula statichandgesturerecognitionbasedonconvolutionalneuralnetworks |