Efficient real-time radial distortion correction for UAVs

Marcus Valtonen Ornhag, Patrik Persson, Marten Wadenback, Kalle Astrom, Anders Heyden

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review


In this paper we present a novel algorithm for onboard radial distortion correction for unmanned aerial vehicles (UAVs) equipped with an inertial measurement unit (IMU), that runs in real-time. This approach makes calibration procedures redundant, thus allowing for exchange of optics extemporaneously. By utilizing the IMU data, the cameras can be aligned with the gravity direction. This allows us to work with fewer degrees of freedom, and opens up for further intrinsic calibration. We propose a fast and robust minimal solver for simultaneously estimating the focal length, radial distortion profile and motion parameters from homographies. The proposed solver is tested on both synthetic and real data, and perform better or on par with state-of-the-art methods relying on pre-calibration procedures. Code available at: https://github.com/marcusvaltonen/HomLib.1

Original languageEnglish
Title of host publication 2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)978-1-6654-0477-8
ISBN (Print)978-0-7381-4266-1
Publication statusPublished - 2021 Jun 14
Event2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021 - Virtual, Online, United States
Duration: 2021 Jan 52021 Jan 9


Conference2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021
Country/TerritoryUnited States
CityVirtual, Online

Bibliographical note

Funding Information:
1 This work was supported by the Swedish Research Council (grant no. 2015-05639), the strategic research projects ELLIIT and eSSENCE, the Swedish Foundation for Strategic Research project, Semantic Mapping and Visual Navigation for Smart Robots (grant no. RIT15-0038), and Wal-lenberg AI, Autonomous Systems and Software Program (WASP) funded by Knut and Alice Wallenberg Foundation.

Publisher Copyright:
© 2021 IEEE.

Subject classification (UKÄ)

  • Mathematics
  • Computer Vision and Robotics (Autonomous Systems)


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