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| Content Provider | IET Digital Library |
|---|---|
| Author | Han, Junwei Awad, George Sutherland, Alistair |
| Abstract | This study addresses the problem of vision-based sign language recognition, which is to translate signs to English. The authors propose a fully automatic system that starts with breaking up signs into manageable subunits. A variety of spatiotemporal descriptors are extracted to form a feature vector for each subunit. Based on the obtained features, subunits are clustered to yield codebooks. A boosting algorithm is then applied to learn a subset of weak classifiers representing discriminative combinations of features and subunits, and to combine them into a strong classifier for each sign. A joint learning strategy is also adopted to share subunits across sign classes, which leads to a more efficient classification. Experimental results on real-world hand gesture videos demonstrate the proposed approach is promising to build an effective and scalable system. |
| Starting Page | 70 |
| Ending Page | 80 |
| Page Count | 11 |
| ISSN | 17519659 |
| Volume Number | 7 |
| e-ISSN | 17519667 |
| Issue Number | Issue 1, Feb (2013) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-ipr/7/1 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2012.0273 |
| Journal | IET Image Processing |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Boosted Subunit Computer Vision Computer Vision And Image Processing Technique English Feature Extraction Feature Vector Hand Gesture Video Handicapped Aids Image Classification Image Recognition Joint Learning Strategy Language Translation Learning in AI Machine Translation Natural Language Processing Pattern Clustering Sign Language Recognition Spatiotemporal Descriptor Extraction Subunit Clustering Vector Video Signal Processing Vision-based Sign Language Recognition |
| Content Type | Text |
| Resource Type | Article |
| Subject | Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software |
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