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Camera self-calibration with lens distortion from a single image / Dan Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)
[article]
Titre : Camera self-calibration with lens distortion from a single image Type de document : Article/Communication Auteurs : Dan Liu, Auteur ; Xuejun Liu, Auteur ; Meizhen Wang, Auteur Année de publication : 2016 Article en page(s) : pp 325 - 334 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] auto-étalonnage
[Termes IGN] contrainte géométrique
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] photogrammétrie terrestreRésumé : (Auteur) This paper presents an effective approach for self-calibration with lens distortion using a single image combined with geometric constraints including vanishing points and ellipses. To improve the accuracy of self-calibration, radial distortion and distortion center are included in the calibration procedure. First, assuming image center as the symmetric center, the first radial distortion coefficient and vanishing points are simultaneously optimized from line segments in the image. Second, by utilizing the optimized vanishing points and extracted ellipse, principal distance and principal point are estimated. Last, distortion center is set as the current calculated principal point, and the above steps are then repeated until the principal point reaches a stable solution. Extensive quantitative and qualitative studies of the approach are performed. The experiments pertaining to simulated and real images demonstrate that the approach is effective and suitable and that the approach obtains satisfactory results. Numéro de notice : A2016-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.5.325 En ligne : http://dx.doi.org/10.14358/PERS.82.5.325 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81274
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 5 (May 2016) . - pp 325 - 334[article]