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Real-time Sign Language Letter and Word Recognition from Depth Data

D. Uebersax and J. Gall and M. Van den Bergh and L. Van Gool
IEEE Workshop on Human Computer Interaction: Real-Time Vision Aspects of Natural User Interfaces
2011

Abstract

In this work, we present a system for recognizing letters and finger-spelled words of the American sign language (ASL) in real-time. To this end, the system segments the hand and estimates the hand orientation from captured depth data. The letter classification is based on average neighborhood margin maximization and relies on the segmented depth data of the hands. For word recognition, the letter confidences are aggregated. Furthermore, the word recognition is used to improve the letter recognition by updating the training examples of the letter classifiers on-line.


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@InProceedings{eth_biwi_00861,
  author = {D. Uebersax and J. Gall and M. Van den Bergh and L. Van Gool},
  title = {Real-time Sign Language Letter and Word Recognition from Depth Data},
  booktitle = {IEEE Workshop on Human Computer Interaction: Real-Time Vision Aspects of Natural User Interfaces},
  year = {2011},
  keywords = {}
}