Efficient Radial Distortion Correction for Planar Motion
(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.
(Less)
- author
- Örnhag, Marcus Valtonen LU
- organization
- publishing date
- 2020
- 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}}, }