Radially-Distorted Conjugate Translations
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Radially-Distorted Conjugate Translations
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Radially-Distorted Conjugate Translations
Popis výsledku anglicky
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.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
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
Počet stran výsledku
9
Strana od-do
1993-2001
Název nakladatele
IEEE
Místo vydání
Piscataway, NJ
Místo konání akce
Salt Lake City
Datum konání akce
19. 6. 2018
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000457843602013