The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Spelling it out: Real-time ASL fingerspelling recognition
Abstract
This article presents an interactive hand shape recognition user interface for American Sign Language (ASL) finger-spelling. The system makes use of a Microsoft Kinect device to collect appearance and depth images, and of the OpenNI+NITE framework for hand detection and tracking. Hand-shapes corresponding to letters of the alphabet are characterized using appearance and depth images and classified using random forests. We compare classification using appearance and depth images, and show a combination of both lead to best results, and validate on a dataset of four different users. This hand shape detection works in real-time and is integrated in an interactive user interface allowing the signer to select between ambiguous detections and integrated with an English dictionary for efficient writing.
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Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Daugman, J. G. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.001160 · Cited by 3,219
Cited by
Survey on 3D Hand Gesture Recognition
Cheng, H., Yang, L., & Liu, Z. (2016) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2015.2469551 · Cited by 344
Static and Dynamic Hand Gesture Recognition in Depth Data Using Dynamic Time Warping
Plouffe, G., & Cretu, A.-M. (2016) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2015.2498560 · Cited by 266
Paul, A. J., Mohan, P., & Sehgal, S. (2020) · 2020 IEEE Recent Advances in Intelligent Computational Systems (RAICS) · doi:10.1109/raics51191.2020.9332480 · Cited by 32
ASL champ!: a virtual reality game with deep-learning driven sign recognition
Alam, M. S., Lamberton, J., Wang, J., Leannah, C., Miller, S., Palagano, J., Bastion, M. D., Smith, H. L., Malzkuhn, M., & Quandt, L. C. (2024) · Computers & Education: X Reality · doi:10.1016/j.cexr.2024.100059 · Cited by 19
Metadata
- Authors
- Pugeault, N., & Bowden, R.
- Venue
- 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)
- Publisher
- IEEE
- Published
- 2011-11
- Pages
- 1114-1119
- ISSN
- 2473-9936 (ISSN-L)
- OpenAlex
- W1993928670
- Cited by
- 415
- References
- 2
- FWCI
- 11.94
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Pugeault, N., & Bowden, R. (2011). Spelling it out: Real-time ASL fingerspelling recognition. 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops). https://doi.org/10.1109/iccvw.2011.6130290
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
