Efficient real-time radial distortion correction for UAVs

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

doi:10.1109/WACV48630.2021.00179

Efficient real-time radial distortion correction for UAVs

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

Linköping University

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

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

Originalspråk	engelska
Titel på värdpublikation	2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
Förlag	IEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor	1750-1759
Antal sidor	10
ISBN (elektroniskt)	978-1-6654-0477-8
ISBN (tryckt)	978-0-7381-4266-1
DOI	https://doi.org/10.1109/WACV48630.2021.00179
Status	Published - 2021 juni 14
Evenemang	2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021 - Virtual, Online, USA Varaktighet: 2021 jan. 5 → 2021 jan. 9

Konferens

Konferens	2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021
Land/Territorium	USA
Ort	Virtual, Online
Period	2021/01/05 → 2021/01/09

Bibliografisk information

Publisher Copyright:
© 2021 IEEE.

Ämnesklassifikation (UKÄ)

Matematik
Datorseende och robotik (autonoma system)

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10.1109/WACV48630.2021.00179

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1 Doktorsavhandling (sammanläggning)

Robust Estimation of Motion Parameters and Scene Geometry: Minimal Solvers and Convexification of Regularisers for Low-Rank Approximation
Bidragets översatta titel : Robust skattning av rörelseparametrar och 3D-geometri: Minimala lösare och konvexifiering av minimerare för långrangsapproximationValtonen Örnhag, M., 2021, Lund University, Faculty of Engineering. 387 s.
Forskningsoutput: Avhandling › Doktorsavhandling (sammanläggning)

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Fil

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@inproceedings{0b4ee6f9f95948ff9f49570f3b949305,

title = "Efficient real-time radial distortion correction for UAVs",

abstract = "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",

author = "Ornhag, {Marcus Valtonen} and Patrik Persson and Marten Wadenback and Kalle Astrom and Anders Heyden",

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: {\textcopyright} 2021 IEEE.; 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021 ; Conference date: 05-01-2021 Through 09-01-2021",

year = "2021",

month = jun,

day = "14",

doi = "10.1109/WACV48630.2021.00179",

language = "English",

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Ornhag, MV, Persson, P, Wadenback, M, Astrom, K & Heyden, A 2021, Efficient real-time radial distortion correction for UAVs. i 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE - Institute of Electrical and Electronics Engineers Inc., s. 1750-1759, 2021 IEEE Winter Conference on Applications of Computer Vision, WACV 2021, Virtual, Online, USA, 2021/01/05. https://doi.org/10.1109/WACV48630.2021.00179

Efficient real-time radial distortion correction for UAVs. / Ornhag, Marcus Valtonen; Persson, Patrik; Wadenback, Marten et al.
2021 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE - Institute of Electrical and Electronics Engineers Inc., 2021. s. 1750-1759.

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

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AU - Persson, Patrik

AU - Wadenback, Marten

AU - Astrom, Kalle

AU - Heyden, Anders

N1 - 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.

PY - 2021/6/14

Y1 - 2021/6/14

N2 - 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

AB - 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

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ER -

Efficient real-time radial distortion correction for UAVs

Sammanfattning

Konferens

Bibliografisk information

Ämnesklassifikation (UKÄ)

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Forskningsoutput

Robust Estimation of Motion Parameters and Scene Geometry: Minimal Solvers and Convexification of Regularisers for Low-Rank Approximation

Citera det här