Novel Feature Extraction and Classification Technique for Sensor-Based Continuous Arabic Sign Language Recognition
This paper proposes a novel approach to continuous Arabic Sign Language recognition. We use a dataset which contains 40 sentences composed from 80 sign language words. The dataset is collected using sensor-based gloves. We propose a novel set of features suitable for sensor readings based on covaria...
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| Other Authors: | , |
| Format: | article |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/11073/21379 |
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