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Sensor Fusion for Augmented Reality
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2007 (English)Report (Other academic)
Abstract [en]

In Augmented Reality (AR), the position and orientation of the camera have to be estimated with high accuracy and low latency. This nonlinear estimation problem is studied in the present paper. The proposed solution makes use of measurements from inertial sensors and computer vision. These measurements are fused using a Kalman filtering framework, incorporating a rather detailed model for the dynamics of the camera. Experiments show that the resulting filter provides good estimates of the camera motion, even during fast movements.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2007. , 9 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2765
Keyword [en]
Sensor fusion, Kalman Filter, Augmented Reality, Computer Vision, Inertial Navigation.
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56117ISRN: LiTH-ISY-R-2765OAI: oai:DiVA.org:liu-56117DiVA: diva2:316814
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-08-07Bibliographically approved

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Authority records BETA

Hol, JeroenSchön, ThomasGustafsson, Fredrik

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf