Evaluating Sign Language Recognition Using the Myo Armband

被引：64
作者：
Abreu, Joao Gabriel [1 ]
Teixeira, Joao Marcelo [2 ]
Figueiredo, Lucas Silva [1 ]
Teichrieb, Veronica [1 ]
机构：
[1] Univ Fed Pernambuco, CIn, Voxar Labs, Recife, PE, Brazil
[2] Univ Fed Rural Pernambuco, DEINFO, Voxar Labs, Recife, PE, Brazil
来源：
2016 18TH SYMPOSIUM ON VIRTUAL AND AUGMENTED REALITY (SVR 2016) | 2016年
关键词：
gesture recognition; support vector machine; sign language; LIBRAS;
D O I：
10.1109/SVR.2016.21
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The successful recognition of sign language gestures by computer systems would greatly improve communications between the deaf and the hearers. This work evaluates the usage of electromyogram (EMG) data provided by the Myo armband as features for classification of 20 stationary letter gestures from the Brazilian Sign Language (LIBRAS) alphabet. The classification was performed by binary Support Vector Machines (SVMs), trained with a one-vs-all strategy. The results obtained show that it is possible to identify the gestures, but substantial limitations were found that would need to be tackled by further studies.
引用
收藏
页码：64 / 70
页数：7
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