Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer

Taiwan Sign Language Recognition System Using LC-KSVD Sparse Coding Method

Authors
Ching-Tang Hsieh, Hsing-Che Liou, Li-Ming Chen
Corresponding Author
Ching-Tang Hsieh
Available Online June 2016.
DOI
10.2991/mmebc-16.2016.112How to use a DOI?
Keywords
Sign Language; Recognition System; Sparse Coding; LC-KSVD
Abstract

Sign language, for deaf-impaired people, plays an important role in communication. In this paper, we devise a Taiwan Sign Language recognition system. We use the Kinect2 sensor to get data from 94 sign morphemes shown once by 4 people, and extract hand shape features and trajectory features from depth images and joints of the body skeleton. Finally, we have each sign morpheme dictionary trained by label consistent K-SVD (LC-KSVD) sparse coding algorithm for recognition. Experiments show our system performs well and the accuracy achieves 99.47% in close test.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-210-7
ISSN
2352-5401
DOI
10.2991/mmebc-16.2016.112How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ching-Tang Hsieh
AU  - Hsing-Che Liou
AU  - Li-Ming Chen
PY  - 2016/06
DA  - 2016/06
TI  - Taiwan Sign Language Recognition System Using LC-KSVD Sparse Coding Method
BT  - Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer
PB  - Atlantis Press
SP  - 519
EP  - 523
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmebc-16.2016.112
DO  - 10.2991/mmebc-16.2016.112
ID  - Hsieh2016/06
ER  -