Recognition of Signed Expressions Using Cluster-Based Segmentation of Time Series

  • Mariusz Oszust
  • Marian Wysocki
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 84)


The paper considers automatic visual recognition of signed expressions. The proposed method is based on modeling gestures with subunits, which is similar to modeling speech by means of phonemes. To define the subunits a data-driven procedure is applied. The procedure consists in partitioning time series, extracted from video, into subsequences which form homogeneous groups. The cut points are determined by an evolutionary optimization procedure based on multicriteria quality assessment of the resulting clusters. In the paper the problem is formulated, its solution method is proposed and experimentally verified on a database of 100 Polish words.


Hide Markov Model Dynamic Time Warping Multiobjective Optimization Problem Polish Sign Language Cluster Validity Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Mariusz Oszust
    • 1
  • Marian Wysocki
    • 1
  1. 1.Department of Computer and Control EngineeringRzeszow University of TechnologyRzeszowPoland

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