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Image Processing and Communications Challenges 2 pp 167–174Cite as

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

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 84))

Summary

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.

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Author information

Authors and Affiliations

  1. Department of Computer and Control Engineering, Rzeszow University of Technology, W. Pola 2, 35-959, Rzeszow, Poland

    Mariusz Oszust & Marian Wysocki

Authors
  1. Mariusz Oszust
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  2. Marian Wysocki
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Editor information

Editors and Affiliations

  1. University of Technology and Life Sciences, Kordeckiego 20, 85-225, Bydgoszcz, Poland

    Ryszard S. Choraś

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Oszust, M., Wysocki, M. (2010). Recognition of Signed Expressions Using Cluster-Based Segmentation of Time Series. In: Choraś, R.S. (eds) Image Processing and Communications Challenges 2. Advances in Intelligent and Soft Computing, vol 84. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16295-4_19

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  • DOI: https://doi.org/10.1007/978-3-642-16295-4_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16294-7

  • Online ISBN: 978-3-642-16295-4

  • eBook Packages: EngineeringEngineering (R0)

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