The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
A real-time continuous gesture recognition system for sign language
Abstract
A large vocabulary sign language interpreter is presented with real-time continuous gesture recognition of sign language using a data glove. Sign language, which is usually known as a set of natural language with formal semantic definitions and syntactic rules, is a large set of hand gestures that are daily used to communicate with the hearing impaired. The most critical problem, end-point detection in a stream of gesture input is first solved and then statistical analysis is done according to four parameters in a gesture: posture, position, orientation, and motion. The authors have implemented a prototype system with a lexicon of 250 vocabularies and collected 196 training sentences in Taiwanese Sign Language (TWL). This system uses hidden Markov models (HMMs) for 51 fundamental postures, 6 orientations, and 8 motion primitives. In a signer-dependent way, a sentence of gestures based on these vocabularies can be continuously recognized in real-time and the average recognition rate is 80.4%,.
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Cited by
A review of hand gesture and sign language recognition techniques
Cheok, M. J., Omar, Z., & Jaward, M. H. (2019) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-017-0705-5 · Cited by 600
Koller, O., Forster, J., & Ney, H. (2015) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2015.09.013 · Cited by 533
Hand gesture recognition using a real-time tracking method and hidden Markov models
Chen, F.-S., Fu, C.-M., & Huang, C.-L. (2003) · Image and Vision Computing · doi:10.1016/s0262-8856(03)00070-2 · Cited by 507
Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective
Bragg, D., Koller, O., Bellard, M., Berke, L., Boudreault, P., Braffort, A., Caselli, N., Huenerfauth, M., Kacorri, H., Verhoef, T., et al. (2019) · Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3308561.3353774 · Cited by 422
A Framework for Recognizing the Simultaneous Aspects of American Sign Language
Vogler, C., & Metaxas, D. (2001) · Computer Vision and Image Understanding · doi:10.1006/cviu.2000.0895 · Cited by 309
Metadata
- Authors
- Liang, R.-H., & Ouhyoung, M.
- Venue
- Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-27
- Pages
- 558-567
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2125834953
- Cited by
- 435
- References
- 11
- FWCI
- 14.73
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Liang, R.-H., & Ouhyoung, M. (2002). A real-time continuous gesture recognition system for sign language. Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition. https://doi.org/10.1109/afgr.1998.671007
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