Static Hand Gesture Recognition Based on Convolutional Neural Networks
Joint Authors
Pinto, Raimundo F.
Borges, Carlos D. B.
Almeida, Antônio M. A.
Paula, Iális C.
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-10-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Pinto, Raimundo F.& Borges, Carlos D. B.& Almeida, Antônio M. A.& Paula, Iális C.. 2019. Static Hand Gesture Recognition Based on Convolutional Neural Networks. Journal of Electrical and Computer Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1173731
Modern Language Association (MLA)
Pinto, Raimundo F.…[et al.]. Static Hand Gesture Recognition Based on Convolutional Neural Networks. Journal of Electrical and Computer Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1173731
American Medical Association (AMA)
Pinto, Raimundo F.& Borges, Carlos D. B.& Almeida, Antônio M. A.& Paula, Iális C.. Static Hand Gesture Recognition Based on Convolutional Neural Networks. Journal of Electrical and Computer Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1173731
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1173731