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Exercise Recognition Using Averaged Hidden Markov Models

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

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Abstract

This paper presents a novel learning algorithm for Hidden Markov Models (HMMs) based on multiple learning sequences. For each activity a few left-to-right HMMs are created and then averaged into singular model. Averaged models’ structure is defined by a proposed Sequences Concatenation Algorithm which has been included in this paper. Also the modification of action recognition algorithm for such averaged models has been described.

The experiments have been conducted for the problem of modeling and recognition of chosen 13 warm-up exercises. The input data have been collected using the depth sensor Microsoft Kinect 2.0. The experiments results confirm that an averaged model combines the features of all component models and thus recognizes more sequences. The obtained models do not confuse modeled activities with others.

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Acknowledgment

This work was supported by the statutory funds of the Faculty of Electronics 0402/0104/16, Wroclaw University of Science and Technology, Wroclaw, Poland.

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Authors and Affiliations

  1. Faculty of Electronics, Wroclaw University of Science and Technology, Wroclaw, Poland

    Aleksandra Postawka

Authors
  1. Aleksandra Postawka
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Correspondence to Aleksandra Postawka .

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Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Postawka, A. (2017). Exercise Recognition Using Averaged Hidden Markov Models. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_14

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  • DOI: https://doi.org/10.1007/978-3-319-59060-8_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59059-2

  • Online ISBN: 978-3-319-59060-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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