A Review of the Hand Gesture Recognition System: Current Progress and Future Directions

This paper reviewed the sign language research in the vision-based hand gesture recognition system from 2014 to 2020. Its objective is to identify the progress and what needs more attention. We have extracted a total of 98 articles from well-known online databases using selected keywords. The review...

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Autores principales:	Noraini Mohamed, Mumtaz Begum Mustafa, Nazean Jomhari
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Classification feature extraction dynamic hand gesture recognition sign language recognition vision-based hand gesture recognition accuracy Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/7add950436704d2aab06a59893d413b3
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spelling	oai:doaj.org-article:7add950436704d2aab06a59893d413b32021-12-03T00:00:39ZA Review of the Hand Gesture Recognition System: Current Progress and Future Directions2169-353610.1109/ACCESS.2021.3129650https://doaj.org/article/7add950436704d2aab06a59893d413b32021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9622242/https://doaj.org/toc/2169-3536This paper reviewed the sign language research in the vision-based hand gesture recognition system from 2014 to 2020. Its objective is to identify the progress and what needs more attention. We have extracted a total of 98 articles from well-known online databases using selected keywords. The review shows that the vision-based hand gesture recognition research is an active field of research, with many studies conducted, resulting in dozens of articles published annually in journals and conference proceedings. Most of the articles focus on three critical aspects of the vision-based hand gesture recognition system, namely: data acquisition, data environment, and hand gesture representation. We have also reviewed the performance of the vision-based hand gesture recognition system in terms of recognition accuracy. For the signer dependent, the recognition accuracy ranges from 69% to 98%, with an average of 88.8% among the selected studies. On the other hand, the signer independent’s recognition accuracy reported in the selected studies ranges from 48% to 97%, with an average recognition accuracy of 78.2%. The lack in the progress of continuous gesture recognition could indicate that more work is needed towards a practical vision-based gesture recognition system.Noraini MohamedMumtaz Begum MustafaNazean JomhariIEEEarticleClassificationfeature extractiondynamic hand gesture recognitionsign language recognitionvision-based hand gesturerecognition accuracyElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 157422-157436 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Classification feature extraction dynamic hand gesture recognition sign language recognition vision-based hand gesture recognition accuracy Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Classification feature extraction dynamic hand gesture recognition sign language recognition vision-based hand gesture recognition accuracy Electrical engineering. Electronics. Nuclear engineering TK1-9971 Noraini Mohamed Mumtaz Begum Mustafa Nazean Jomhari A Review of the Hand Gesture Recognition System: Current Progress and Future Directions
description	This paper reviewed the sign language research in the vision-based hand gesture recognition system from 2014 to 2020. Its objective is to identify the progress and what needs more attention. We have extracted a total of 98 articles from well-known online databases using selected keywords. The review shows that the vision-based hand gesture recognition research is an active field of research, with many studies conducted, resulting in dozens of articles published annually in journals and conference proceedings. Most of the articles focus on three critical aspects of the vision-based hand gesture recognition system, namely: data acquisition, data environment, and hand gesture representation. We have also reviewed the performance of the vision-based hand gesture recognition system in terms of recognition accuracy. For the signer dependent, the recognition accuracy ranges from 69% to 98%, with an average of 88.8% among the selected studies. On the other hand, the signer independent’s recognition accuracy reported in the selected studies ranges from 48% to 97%, with an average recognition accuracy of 78.2%. The lack in the progress of continuous gesture recognition could indicate that more work is needed towards a practical vision-based gesture recognition system.
format	article
author	Noraini Mohamed Mumtaz Begum Mustafa Nazean Jomhari
author_facet	Noraini Mohamed Mumtaz Begum Mustafa Nazean Jomhari
author_sort	Noraini Mohamed
title	A Review of the Hand Gesture Recognition System: Current Progress and Future Directions
title_short	A Review of the Hand Gesture Recognition System: Current Progress and Future Directions
title_full	A Review of the Hand Gesture Recognition System: Current Progress and Future Directions
title_fullStr	A Review of the Hand Gesture Recognition System: Current Progress and Future Directions
title_full_unstemmed	A Review of the Hand Gesture Recognition System: Current Progress and Future Directions
title_sort	review of the hand gesture recognition system: current progress and future directions
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/7add950436704d2aab06a59893d413b3
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A Review of the Hand Gesture Recognition System: Current Progress and Future Directions

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