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Why Would I Want a Gyroscope on my RGB-D Sensor?
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-5698-5983
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2013 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

Many RGB-D sensors, e.g. the Microsoft Kinect, use rolling shutter cameras. Such cameras produce geometrically distorted images when the sensor is moving. To mitigate these rolling shutter distortions we propose a method that uses an attached gyroscope to rectify the depth scans. We also present a simple scheme to calibrate the relative pose and time synchronization between the gyro and a rolling shutter RGB-D sensor. We examine the effectiveness of our rectification scheme by coupling it with the the Kinect Fusion algorithm. By comparing Kinect Fusion models obtained from raw sensor scans and from rectified scans, we demonstrate improvement for three classes of sensor motion: panning motions causes slant distortions, and tilt motions cause vertically elongated or compressed objects. For wobble we also observe a loss of detail, compared to the reconstruction using rectified depth scans. As our method relies on gyroscope readings, the amount of computations required is negligible compared to the cost of running Kinect Fusion.

Place, publisher, year, edition, pages
IEEE , 2013. 68-75 p.
Keyword [en]
RGB-D sensor, rolling shutter, Kinect Fusion, Kinect, calibration
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-87751DOI: 10.1109/WORV.2013.6521916ISBN: 978-1-4673-5647-3 (print)ISBN: 978-1-4673-5646-6 (print)OAI: oai:DiVA.org:liu-87751DiVA: diva2:603474
Conference
IEEE Workshop on Robot Vision 2013, Clearwater Beach, Florida, USA, January 16-17, 2013
Projects
Embodied Visual Object Recognition
Funder
Swedish Research Council, Embodied Visual Object Recognition
Available from: 2013-02-08 Created: 2013-01-22 Last updated: 2015-12-10Bibliographically approved

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Ovrén, HannesForssén, Per-ErikTörnqvist, David

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CiteExportLink to record
Permanent link

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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