Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)

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Dynamic Hand Gesture Recognition Based on Deep Learning for Muslim Elderly Care

Authors
Hadya Ayeisha Marzuki1, *, Noramiza Hashim1
1Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, 63100, Cyberjaya, Selangor, Malaysia
*Corresponding author. Email: 1181101256@student.mmu.edu.my
Corresponding Author
Hadya Ayeisha Marzuki
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-094-7_44How to use a DOI?
Keywords
Dynamic Hand Gesture Recognition; Muslim Elderly Care; CNN-RNN; Transformer
Abstract

Gesture recognition for elderly care is an approach to classify gestures performed by the elderly to convey specific messages. Nursing homes or caretakers are often hired to take care of senior citizens and are responsible to keep them safe. Hence, this study will be useful to assist caretakers in providing needs requested by the elderly when they are absent. A collection of dynamic hand gesture recognition (HGR) datasets consisting of ten gesture classes with 630 videos is used to build the models. The ten gestures will represent requests for help to perform daily activities namely eating, toileting and dressing. Specifically for this research, we have infused Islamic hand gestures such as gestures to perform prayers and read the Quran. In this paper, we adopted the action recognition pre-trained model into the HGR by using CNN RNN and Transformer with CNN models. The result of this study shows that Transformer with CNN model has higher accuracy in recognizing hand gestures compared to CNN-RNN model.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-094-7_44
ISSN
2589-4900
DOI
10.2991/978-94-6463-094-7_44How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Hadya Ayeisha Marzuki
AU  - Noramiza Hashim
PY  - 2022
DA  - 2022/12/27
TI  - Dynamic Hand Gesture Recognition Based on Deep Learning for Muslim Elderly Care
BT  - Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
PB  - Atlantis Press
SP  - 544
EP  - 557
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-094-7_44
DO  - 10.2991/978-94-6463-094-7_44
ID  - Marzuki2022
ER  -