- Title
- An evaluation of hand-based algorithms for sign language recognition
- Creator
- Marais, Marc, Brown, Dane L, Connan, James, Boby, Alden
- Subject
- To be catalogued
- Date
- 2022
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/465124
- Identifier
- vital:76575
- Identifier
- xlink:href="https://ieeexplore.ieee.org/abstract/document/9856310"
- Description
- Sign language recognition is an evolving research field in computer vision, assisting communication between hearing disabled people. Hand gestures contain the majority of the information when signing. Focusing on feature extraction methods to obtain the information stored in hand data in sign language recognition may improve classification accuracy. Pose estimation is a popular method for extracting body and hand landmarks. We implement and compare different feature extraction and segmentation algorithms, focusing on the hands only on the LSA64 dataset. To extract hand landmark coordinates, MediaPipe Holistic is implemented on the sign images. Classification is performed using poplar CNN architectures, namely ResNet and a Pruned VGG network. A separate 1D-CNN is utilised to classify hand landmark coordinates extracted using MediaPipe. The best performance was achieved on the unprocessed raw images using a Pruned VGG network with an accuracy of 95.50%. However, the more computationally efficient model using the hand landmark data and 1D-CNN for classification achieved an accuracy of 94.91%.
- Format
- computer, online resource, application/pdf, 1 online resource (5 pages), pdf
- Publisher
- IEEE Xplore
- Language
- English
- Relation
- IEEE Xplore, Marais, M., Brown, D., Connan, J. and Boby, A., 2022, August. An evaluation of hand-based algorithms for sign language recognition. In 2022 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-6). IEEE, IEEE Xplore p. 555 2014 1573-0921
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the IEEE Xplore Terms of Use Statement (https://ieeexplore.ieee.org/Xplorehelp/overview-of-ieee-xplore/terms-of-use)
- Rights
- Closed Access
- Hits: 2
- Visitors: 2
- Downloads: 0
Collections
Brown, Dane A (Dr)
Connan, James (Mr)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details | SOURCE1 | An evaluation of hand-based algorithms for sign language recognition.pdf | 659 KB | Adobe Acrobat PDF | View Details |