Using Hierarchical Temporal Memory for Recognition of Signed Polish Words

  • Tomasz Kapuscinski
  • Marian Wysocki
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 57)


The paper is concerned with automatic vision-based recognition of hand gestures expressing isolated words of Polish Sign Language (PSL). The Hierarchical Temporal Memory (HTM) [3] is applied. This tool replicates the structural and algorithmic properties of the human neocortex. The gestures are spatio-temporal entities. Therefore we believe the HTM can be able to identify and use the gesture’s subunits (counterparts of phonemes) organized in spatio-temporal hierarchy. The paper discusses the preparation issues of the HTM and presents results of the recognition of 101 words used in everyday life at the doctors and in the post office.


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  1. 1.
    Bauer, B., Kraiss, K.F.: Video-Based Sign Recognition Using Self-Organizing Subunits. In: Proc. Int. Conf. Pattern Recognition, vol. 2, pp. 434–437 (2002)Google Scholar
  2. 2.
    Bowden, D., Windridge, D., Kadir, T., Zisserman, A., Brady, M.: A Linguistic Feature Vector for the Visual Interpretation of Sign Language. In: Proc. 8th Eur. Conf. Comput. Vis., pp. 391–401. Springer, New York (2004)Google Scholar
  3. 3.
    Hawkins, J., Blakeslee, S.: On Intelligence. Times Books, New York (2004)Google Scholar
  4. 4.
    Kapuscinski, T., Wysocki, M.: Automatic Recognition of Signed Polish Expressions. Archives of Control Sciences 15(3) (LI), 251–259 (2006)Google Scholar
  5. 5.
    Kapuscinski, T., Wysocki, M.: Recognition of signed Polish words using visually-oriented subunits. In: Proc. of the 3rd Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics, Poznan, pp. 202–206 (2007)Google Scholar
  6. 6.
    Kapuscinski, T., Wysocki, M.: Automatic Recognition of Signed Polish Expressions Using Visually Oriented Subunits. In: Rutkowski, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J. (eds.) Computational Intelligence: Methods and Applications, pp. 267–278. AOW EXIT, Warszawa (2008)Google Scholar
  7. 7.
    Numenta Platform for Intelligent Computing (NuPIC), Numenta Inc.,
  8. 8.
    Ong, S.C.W., Ranganath, S.: Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning. IEEE Trans. PAMI 27, 873–891 (2005)Google Scholar
  9. 9.
    Szczepankowski, B.: Sign language in school. WSiP, Warszawa (1988) (in Polish)Google Scholar
  10. 10.
    Vogler, C., Metaxas, D.: A Framework for Recognizing the Simultaneous Aspects of American Sign Language. Computer Vision and Image Understanding, 358–384 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Tomasz Kapuscinski
    • 1
  • Marian Wysocki
    • 1
  1. 1.Department of Computer and Contol EngineeringRzeszow University of TechnologyPoland

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