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Accelerometer Based Gesture Recognition Using Continuous HMMs

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Pattern Recognition and Image Analysis (IbPRIA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3522))

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Abstract

This paper presents a gesture recognition system based on continuous hidden Markov models. Gestures here are hand movements which are recorded by a 3D accelerometer embedded in a handheld device. In addition to standard hidden Markov model classifier, the recognition system has a preprocessing step which removes the effect of device orientation from the data. The performance of the recognizer is evaluated in both user dependent and user independent cases. The effects of sample resolution and sampling rate are studied in the user dependent case.

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Author information

Authors and Affiliations

  1. Nokia Research Center, P.O. Box 100, FIN-33721, Tampere

    Timo Pylvänäinen

Authors
  1. Timo Pylvänäinen
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Editor information

Editors and Affiliations

  1. Instituto Superior Técnico & Instituto de Sistemas e Robótica, 1049-001, Lisboa, Portugal

    Jorge S. Marques

  2. ETSI Informática y e Telecomunicación, University of Granada, 18071, Granada, Spain

    Nicolás Pérez de la Blanca

  3. CERENA-Centro de Recursos Naturais e Ambiente, Instituto Superior Técnico, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Pedro Pina

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© 2005 Springer-Verlag Berlin Heidelberg

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Pylvänäinen, T. (2005). Accelerometer Based Gesture Recognition Using Continuous HMMs. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3522. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492429_77

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  • DOI: https://doi.org/10.1007/11492429_77

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26153-7

  • Online ISBN: 978-3-540-32237-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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