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IMU Drift Reduction for Augmented Reality Applications

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Augmented and Virtual Reality (AVR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9254))

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Abstract

Pose estimation is a major task in any augmented reality (AR) application. Sensors like inertial measurement units (IMUs) and cameras are used for this purpose. IMU provides fast data, from which a pose can be determined with fewer calculations. In most cases, this data is influenced by drift. This paper investigates a drift reduction technique on positions calculated from accelerometer data and the result shows that this technique significantly reduces drift in fast dynamic movements. Furthermore, this drift reduced IMU pose can be fused with low pose updates from vision algorithms to improve the accuracy and speed suitable for AR applications.

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Notes

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Acknowledgements

The authors wish to thank all other members of the EDUSAFE consortium. This research has been supported by a Marie Curie Initial Training Network Fellowship of the European Commission FP7 Programme under contract number PITN-GA-2012-316919-EDUSAFE.

Author information

Authors and Affiliations

  1. European Organization for Nuclear Research, CERN, Geneva, Switzerland

    Lakshmi Prabha Nattamai Sekar, Alexander Santos & Olga Beltramello

  2. University of Rome Tor Vergata, Rome, Italy

    Lakshmi Prabha Nattamai Sekar

Authors
  1. Lakshmi Prabha Nattamai Sekar
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  2. Alexander Santos
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  3. Olga Beltramello
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Corresponding author

Correspondence to Lakshmi Prabha Nattamai Sekar .

Editor information

Editors and Affiliations

  1. Department of Engineering for Innovation, University of Salento, Lecce, Italy

    Lucio Tommaso De Paolis

  2. Department of Engineering for Innovation, University of Salento, Lecce, Italy

    Antonio Mongelli

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Nattamai Sekar, L.P., Santos, A., Beltramello, O. (2015). IMU Drift Reduction for Augmented Reality Applications. In: De Paolis, L., Mongelli, A. (eds) Augmented and Virtual Reality. AVR 2015. Lecture Notes in Computer Science(), vol 9254. Springer, Cham. https://doi.org/10.1007/978-3-319-22888-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-22888-4_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22887-7

  • Online ISBN: 978-3-319-22888-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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