Abstract
The paper considers partitioning time series into subsequences which form homogeneous groups. To determine the cut points an evolutionary optimization procedure based on multicriteria quality assessment of the resulting clusters is applied. The problem is motivated by automatic recognition of signed expressions, based on modeling gestures with subunits, which is similar to modeling speech by means of phonemes. In the paper the problem is formulated, its solution method is proposed and experimentally verified.
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Oszust, M., Wysocki, M. (2010). Determining Subunits for Sign Language Recognition by Evolutionary Cluster-Based Segmentation of Time Series. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artifical Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13232-2_23
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DOI: https://doi.org/10.1007/978-3-642-13232-2_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13231-5
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