liu.seSearch for publications in DiVA
Change search
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
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.
2009 (English)Report (Other academic)
Abstract [en]

The problem of estimating the position and orientation (pose) of a camera is approached by fusing measurements from inertial sensors (accelerometers and rate gyroscopes) and a camera. The sensor fusion approach described in this contribution is based on nonlinear filtering using the measurements from these complementary sensors. This way, accurate and robust pose estimates are available for the primary purpose of augmented reality applications, but with the secondary effect of reducing computation time and improving the performance in vision processing. A real-time implementation of a nonlinear filter is described, using a dynamic model for the 22 states, where 100 Hz inertial measurements and 12.5 Hz vision measurements are processed. An example where an industrial robot is used to move the sensor unit, possessing almost perfect precision and repeatability, is presented. The results show that position and orientation accuracy is sufficient for a number of augmented reality applications.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2009. , 3 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2875
Keyword [en]
Sensor fusion, Nonlinear filtering, Tracking, Kalman filter, Augmented reality
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56191ISRN: LiTH-ISY-R-2875OAI: oai:DiVA.org:liu-56191DiVA: diva2:316979
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-08-11Bibliographically approved

Open Access in DiVA

fulltext(235 kB)114 downloads
File information
File name FULLTEXT01.pdfFile size 235 kBChecksum SHA-512
6b061339b81815ce41dadc9c881974cb8ccc6d7ac2fcd4f3bddce08496e547bfde310e226185ac5472a8cddefaf371d194f2ed9a0e4f6e7cac50329b16808420
Type fulltextMimetype application/pdf

Authority records BETA

Gustafsson, FredrikSchön, ThomasHol, Jeroen

Search in DiVA

By author/editor
Gustafsson, FredrikSchön, ThomasHol, Jeroen
By organisation
Automatic ControlThe Institute of Technology
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 114 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 170 hits
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