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Towards an Automatic Sign Language Recognition System Using Subunits

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Gesture and Sign Language in Human-Computer Interaction (GW 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2298))

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Abstract

This paper is concerned with the automatic recognition of German continuous sign language. For the most user-friendliness only one single color video camera is used for image recording. The statistical approach is based on the Bayes decision rule for minimum error rate. Following speech recognition system design, which are in general based on subunits, here the idea of an automatic sign language recognition system using subunits rather than models for whole signs will be outlined. The advantage of such a system will be a future reduction of necessary training material. Furthermore, a simplified enlargement of the existing vocabulary is expected. Since it is difficult to define subunits for sign language, this approach employs totally self-organized subunits called fenone. K-means algorithm is used for the definition of such fenones. The software prototype of the system is currently evaluated in experiments.

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Author information

Authors and Affiliations

  1. Department of Technical Computer Science, Aachen University of Technology (RWTH), Ahornstrasse 55, D-52074, Aachen, Germany

    Britta Bauer & Kraiss Karl-Friedrich

Authors
  1. Britta Bauer
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  2. Kraiss Karl-Friedrich
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Editor information

Editors and Affiliations

  1. Technische Fakultät, Universität Bielefeld, 33594, Bielefeld, Germany

    Ipke Wachsmuth  & Timo Sowa  & 

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© 2002 Springer-Verlag Berlin Heidelberg

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Bauer, B., Karl-Friedrich, K. (2002). Towards an Automatic Sign Language Recognition System Using Subunits. In: Wachsmuth, I., Sowa, T. (eds) Gesture and Sign Language in Human-Computer Interaction. GW 2001. Lecture Notes in Computer Science(), vol 2298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47873-6_7

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  • DOI: https://doi.org/10.1007/3-540-47873-6_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43678-2

  • Online ISBN: 978-3-540-47873-7

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