Automatic recognition of fingerspelled words in British Sign Language

Stephan Liwicki, M. Everingham
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引用次数: 132

Abstract

We investigate the problem of recognizing words from video, fingerspelled using the British Sign Language (BSL) fingerspelling alphabet. This is a challenging task since the BSL alphabet involves both hands occluding each other, and contains signs which are ambiguous from the observer's viewpoint. The main contributions of our work include: (i) recognition based on hand shape alone, not requiring motion cues; (ii) robust visual features for hand shape recognition; (iii) scalability to large lexicon recognition with no re-training. We report results on a dataset of 1,000 low quality webcam videos of 100 words. The proposed method achieves a word recognition accuracy of 98.9%.
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自动识别手指拼写单词在英国手语
我们研究了用英国手语(BSL)拼写字母来识别视频中单词的问题。这是一项具有挑战性的任务,因为BSL字母表涉及双手互相遮挡,并且从观察者的角度来看包含模棱两可的符号。我们工作的主要贡献包括:(i)仅基于手部形状的识别,不需要动作线索;(ii)手部形状识别的鲁棒视觉特征;(iii)无需重新训练即可扩展到大型词典识别。我们报告了1000个低质量的100个单词的网络摄像头视频的数据集的结果。该方法的单词识别准确率达到98.9%。
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