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FGR
2008
IEEE

Bi-channel sensor fusion for automatic sign language recognition

9 years 4 months ago
Bi-channel sensor fusion for automatic sign language recognition
In this paper, we investigate the mutual-complementary functionality of accelerometer (ACC) and electromyogram (EMG) for recognizing seven word-level sign vocabularies in German Sign Language (GSL). Results are discussed for the single channels and for feature-level fustion for the bichannel sensor data. For the subject-dependent condition, this fusion method proves to be effective. Most relevant features for all subjects are extracted and their universal effectiveness is proven with a high average accuracy for the single subjects. Additionally, results are given for the subjectindependent condition, where subjective differences do not allow for high recognition rates. Finally we discuss a problem of feature-level fusion caused by high disparity between accuracies of each single channel classification.
Jonghwa Kim, Johannes Wagner, Matthias Rehm, Elisa
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where FGR
Authors Jonghwa Kim, Johannes Wagner, Matthias Rehm, Elisabeth André
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