Radially-Distorted Conjugate Translations
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00327005" target="_blank" >RIV/68407700:21230/18:00327005 - isvavai.cz</a>
Result on the web
<a href="http://openaccess.thecvf.com/content_cvpr_2018/papers_backup/Pritts_Radially-Distorted_Conjugate_Translations_CVPR_2018_paper.pdf" target="_blank" >http://openaccess.thecvf.com/content_cvpr_2018/papers_backup/Pritts_Radially-Distorted_Conjugate_Translations_CVPR_2018_paper.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2018.00213" target="_blank" >10.1109/CVPR.2018.00213</a>
Alternative languages
Result language
angličtina
Original language name
Radially-Distorted Conjugate Translations
Original language description
This paper introduces the first minimal solvers that jointly solve for affine-rectification and radial lens distortion from coplanar repeated patterns. Even with imagery from moderately distorted lenses, plane rectification using the pinhole camera model is inaccurate or invalid. The proposed solvers incorporate lens distortion into the camera model and extend accurate rectification to wide-angle imagery, which is now common from consumer cameras. The solvers are derived from constraints induced by the conjugate translations of an imaged scene plane, which are integrated with the division model for radial lens distortion. The hidden-variable trick with ideal saturation is used to reformulate the constraints so that the solvers generated by the Gröbner-basis method are stable, small and fast. Rectification and lens distortion are recovered from either one conjugately translated affine-covariant feature or two independently translated similarity-covariant features. The proposed solvers are used in a RANSAC-based estimator, which gives accurate rectifications after few iterations. The proposed solvers are evaluated against the state-of-the-art and demonstrate significantly better rectifcations on noisy measurements. Qualitative results on diverse imagery demonstrate high-accuracy undistortion and rectification.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CVPR 2018: Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition
ISBN
978-1-5386-6420-9
ISSN
1063-6919
e-ISSN
2575-7075
Number of pages
9
Pages from-to
1993-2001
Publisher name
IEEE
Place of publication
Piscataway, NJ
Event location
Salt Lake City
Event date
Jun 19, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000457843602013