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Towards Robust Framework for On-line Human Activity Reporting Using Accelerometer Readings

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Active Media Technology (AMT 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8610))

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Abstract

This paper investigates subsequent matching approach and feature-based classification for activity recognition using accelerometer readings. Recognition is done by similarity measure based on Dynamic Time Warping (DTW) on each acceleration axis. Ensemble method is proposed and comparative study is executed showing better and more stable results. Our scenario assumes that activity is recognized with very small latency. Results shows that hybrid approach is promising for activity reporting, i.e. different walking patterns, using of tools. The proposed solution is designed to be a part of decision support in fire and rescue actions at the fire ground.

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Author information

Authors and Affiliations

  1. Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland

    Michał Meina & Krzysztof Rykaczewski

  2. Section of Computer Science, The Main School of Fire Service, Warsaw, Poland

    Bartosz Celmer

  3. Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Toruń, Poland

    Michał Meina & Krzysztof Rykaczewski

Authors
  1. Michał Meina
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  2. Bartosz Celmer
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  3. Krzysztof Rykaczewski
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Editor information

Editors and Affiliations

  1. University of Warsaw and Infobright Inc., Poland

    Dominik Ślȩzak

  2. Department of Computer Science, Loughborough University, Loughborough, U.K.

    Gerald Schaefer

  3. Computer Science Department, University of British Columbia, 2366 Main Mall, P.O. Box, Vancouver, B.C., Canada

    Son T. Vuong

  4. Department of Information & Communication Engineering, Inha University, Korea

    Yoo-Sung Kim

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© 2014 Springer International Publishing Switzerland

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Meina, M., Celmer, B., Rykaczewski, K. (2014). Towards Robust Framework for On-line Human Activity Reporting Using Accelerometer Readings. In: Ślȩzak, D., Schaefer, G., Vuong, S.T., Kim, YS. (eds) Active Media Technology. AMT 2014. Lecture Notes in Computer Science, vol 8610. Springer, Cham. https://doi.org/10.1007/978-3-319-09912-5_29

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  • DOI: https://doi.org/10.1007/978-3-319-09912-5_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09911-8

  • Online ISBN: 978-3-319-09912-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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