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Minimal solutions for the rotational alignment of IMU-camera systems using homography constraints

Guan, Banglei und Yu, Qifeng und Fraundorfer, Friedrich (2018) Minimal solutions for the rotational alignment of IMU-camera systems using homography constraints. Computer Vision and Image Understanding, 170, Seiten 79-91. Elsevier. doi: 10.1016/j.cviu.2018.03.001. ISSN 1077-3142.

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Offizielle URL: https://doi.org/10.1016/j.cviu.2018.03.001

Kurzfassung

In this paper, we explore the different minimal case solutions to the rotational alignment of IMU-camera systems using homography constraints. The assumption that a ground plane is visible in the images can easily be created in many situations. This calibration process is relevant to many smart devices equipped with a camera and an inertial measurement unit (IMU), like micro aerial vehicles (MAVs), smartphones and tablets, and it is a fundamental step for vision and IMU data fusion. Our solutions are novel as they compute the rotational alignment of IMU-camera systems by utilizing a first-order rotation approximation and by solving a polynomial equation system derived from homography constraints. These solutions depend on the calibration case with respect to camera motion (general motion case or pure rotation case) and camera parameters (calibrated camera or partially uncalibrated camera). We then demonstrate that the number of matched points in an image pair can vary from 1.5 to 3. This enables us to calibrate using only one relative movement and provide the exact algebraic solution to the problem. The novel minimal case solutions are useful to reduce the computation time and increase the calibration robustness when using Random Sample Consensus (RANSAC) on the point correspondences between two images. Furthermore, a non-linear parameter optimization over all image pairs is performed. In contrast to the previous calibration methods, our solutions do not require any special hardware, and no problems are experienced with one image pair without special motion. Finally, by evaluating our algorithm on both synthetic and real scene data including data obtained from robots, smartphones and MAVs, we demonstrate that our methods are both efficient and numerically stable for the rotational alignment of IMUcamera systems.

elib-URL des Eintrags:https://elib.dlr.de/120649/
Dokumentart:Zeitschriftenbeitrag
Titel:Minimal solutions for the rotational alignment of IMU-camera systems using homography constraints
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Guan, BangleiCollege of Aerospace Science and Engineering, Nat. University of Defense Technology, ChinaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Yu, QifengHunan Provincial Key Laboratory of Image Measurement and Vision Navigation, ChinaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Fraundorfer, Friedrichfriedrich.fraundorfer (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:Februar 2018
Erschienen in:Computer Vision and Image Understanding
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:170
DOI:10.1016/j.cviu.2018.03.001
Seitenbereich:Seiten 79-91
Verlag:Elsevier
ISSN:1077-3142
Status:veröffentlicht
Stichwörter:IMU-camera calibration; Rotational alignment; Minimal solution; Homography constraint; Algebraic solution; Pure rotation
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Verkehrsmanagement (alt)
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V VM - Verkehrsmanagement
DLR - Teilgebiet (Projekt, Vorhaben):V - Vabene++ (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Methodik der Fernerkundung > Photogrammetrie und Bildanalyse
Hinterlegt von: Zielske, Mandy
Hinterlegt am:03 Jul 2018 18:35
Letzte Änderung:06 Sep 2019 15:19

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