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Efficient Radial Distortion Correction for Planar Motion

Örnhag, Marcus Valtonen LU (2020) 9th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2020 In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 12594 LNCS. p.46-63
Abstract

In this paper we investigate simultaneous radial distortion calibration and motion estimation for vehicles travelling parallel to planar surfaces. This is done by estimating the inter-image homography between two poses, as well as the distortion parameter. Radial distortion correction is often performed as a pre-calibration step; however, accurately estimating the distortion profile without special scene requirements may make such procedures obsolete. As many modern day consumer cameras are affected by radial distortion to some degree, there is a great potential to reduce production time, if properly implemented. We devise two polynomial solvers, for radially distorted homographies compatible with different models of planar motion. We... (More)

In this paper we investigate simultaneous radial distortion calibration and motion estimation for vehicles travelling parallel to planar surfaces. This is done by estimating the inter-image homography between two poses, as well as the distortion parameter. Radial distortion correction is often performed as a pre-calibration step; however, accurately estimating the distortion profile without special scene requirements may make such procedures obsolete. As many modern day consumer cameras are affected by radial distortion to some degree, there is a great potential to reduce production time, if properly implemented. We devise two polynomial solvers, for radially distorted homographies compatible with different models of planar motion. We show that the algorithms are numerically stable, and sufficiently fast to be incorporated in a real-time frameworks. Furthermore, we show on both synthetic and real data, that the proposed solvers perform well compared to competing methods.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Homography, Polynomial solvers, Radial distortion correction, Visual odometry
host publication
Pattern Recognition Applications and Methods - 9th International Conference, ICPRAM 2020, Revised Selected Papers
series title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
editor
De Marsico, Maria ; di Baja, Gabriella Sanniti and Fred, Ana
volume
12594 LNCS
pages
18 pages
publisher
Springer Science and Business Media B.V.
conference name
9th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2020
conference location
Valletta, Malta
conference dates
2020-02-22 - 2020-02-24
external identifiers
  • scopus:85146916738
ISSN
1611-3349
0302-9743
ISBN
9783030661243
DOI
10.1007/978-3-030-66125-0_4
language
English
LU publication?
yes
id
05dbf601-b971-4345-8146-6eba23361001
date added to LUP
2023-02-15 15:15:32
date last changed
2024-04-04 16:37:15
@inproceedings{05dbf601-b971-4345-8146-6eba23361001,
  abstract     = {{<p>In this paper we investigate simultaneous radial distortion calibration and motion estimation for vehicles travelling parallel to planar surfaces. This is done by estimating the inter-image homography between two poses, as well as the distortion parameter. Radial distortion correction is often performed as a pre-calibration step; however, accurately estimating the distortion profile without special scene requirements may make such procedures obsolete. As many modern day consumer cameras are affected by radial distortion to some degree, there is a great potential to reduce production time, if properly implemented. We devise two polynomial solvers, for radially distorted homographies compatible with different models of planar motion. We show that the algorithms are numerically stable, and sufficiently fast to be incorporated in a real-time frameworks. Furthermore, we show on both synthetic and real data, that the proposed solvers perform well compared to competing methods.</p>}},
  author       = {{Örnhag, Marcus Valtonen}},
  booktitle    = {{Pattern Recognition Applications and Methods - 9th International Conference, ICPRAM 2020, Revised Selected Papers}},
  editor       = {{De Marsico, Maria and di Baja, Gabriella Sanniti and Fred, Ana}},
  isbn         = {{9783030661243}},
  issn         = {{1611-3349}},
  keywords     = {{Homography; Polynomial solvers; Radial distortion correction; Visual odometry}},
  language     = {{eng}},
  pages        = {{46--63}},
  publisher    = {{Springer Science and Business Media B.V.}},
  series       = {{Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}},
  title        = {{Efficient Radial Distortion Correction for Planar Motion}},
  url          = {{http://dx.doi.org/10.1007/978-3-030-66125-0_4}},
  doi          = {{10.1007/978-3-030-66125-0_4}},
  volume       = {{12594 LNCS}},
  year         = {{2020}},
}