Technical Approaches to Chinese Sign Language Processing: A Review
As with the huge number of deaf-mute people in China is of concern, there is a growing need to integrate them into mainstream society through the use of efficient sign language processing technologies. Sign language processing entails the systematic recognition and translation of sign language image...
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doaj-fe494eb67460463b8672929193c9cbfe2021-04-05T17:11:04ZengIEEEIEEE Access2169-35362019-01-017969269693510.1109/ACCESS.2019.29291748764391Technical Approaches to Chinese Sign Language Processing: A ReviewSuhail Muhammad Kamal0https://orcid.org/0000-0001-8019-6012Yidong Chen1Shaozi Li2Xiaodong Shi3Jiangbin Zheng4School of Informatics, Xiamen University, Xiamen, ChinaSchool of Informatics, Xiamen University, Xiamen, ChinaSchool of Informatics, Xiamen University, Xiamen, ChinaSchool of Informatics, Xiamen University, Xiamen, ChinaSchool of Informatics, Xiamen University, Xiamen, ChinaAs with the huge number of deaf-mute people in China is of concern, there is a growing need to integrate them into mainstream society through the use of efficient sign language processing technologies. Sign language processing entails the systematic recognition and translation of sign language images/videos to text or speech. This survey provides an overview of the most important work on Chinese sign language recognition and translation, discussed its classification, highlights the features explored in sign language recognition research, presents the datasets available, and provides trends for the future research.https://ieeexplore.ieee.org/document/8764391/Sign languageChinese sign language recognitiondeep learningCSL datasetsvision-basedsensor-based |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Suhail Muhammad Kamal Yidong Chen Shaozi Li Xiaodong Shi Jiangbin Zheng |
spellingShingle |
Suhail Muhammad Kamal Yidong Chen Shaozi Li Xiaodong Shi Jiangbin Zheng Technical Approaches to Chinese Sign Language Processing: A Review IEEE Access Sign language Chinese sign language recognition deep learning CSL datasets vision-based sensor-based |
author_facet |
Suhail Muhammad Kamal Yidong Chen Shaozi Li Xiaodong Shi Jiangbin Zheng |
author_sort |
Suhail Muhammad Kamal |
title |
Technical Approaches to Chinese Sign Language Processing: A Review |
title_short |
Technical Approaches to Chinese Sign Language Processing: A Review |
title_full |
Technical Approaches to Chinese Sign Language Processing: A Review |
title_fullStr |
Technical Approaches to Chinese Sign Language Processing: A Review |
title_full_unstemmed |
Technical Approaches to Chinese Sign Language Processing: A Review |
title_sort |
technical approaches to chinese sign language processing: a review |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
As with the huge number of deaf-mute people in China is of concern, there is a growing need to integrate them into mainstream society through the use of efficient sign language processing technologies. Sign language processing entails the systematic recognition and translation of sign language images/videos to text or speech. This survey provides an overview of the most important work on Chinese sign language recognition and translation, discussed its classification, highlights the features explored in sign language recognition research, presents the datasets available, and provides trends for the future research. |
topic |
Sign language Chinese sign language recognition deep learning CSL datasets vision-based sensor-based |
url |
https://ieeexplore.ieee.org/document/8764391/ |
work_keys_str_mv |
AT suhailmuhammadkamal technicalapproachestochinesesignlanguageprocessingareview AT yidongchen technicalapproachestochinesesignlanguageprocessingareview AT shaozili technicalapproachestochinesesignlanguageprocessingareview AT xiaodongshi technicalapproachestochinesesignlanguageprocessingareview AT jiangbinzheng technicalapproachestochinesesignlanguageprocessingareview |
_version_ |
1721540203593596928 |