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dc.contributor.authorSmolic, Aljosa
dc.contributor.authorLutz, Sebastian
dc.contributor.authorDavey, Mark
dc.date.accessioned2020-02-18T16:20:41Z
dc.date.available2020-02-18T16:20:41Z
dc.date.issued2019
dc.date.submitted2019en
dc.identifier.citationLutz, S., Davey, M. & Smolic, A., Deep Convolutional Neural Networks for estimating lens distortion parameters, Irish Machine Vision and Image Processing Conference (IMVIP) 2019en
dc.identifier.otherY
dc.descriptionPUBLISHEDen
dc.description.abstractIn this paper we present a convolutional neural network (CNN) to predict multiple lens distortion parameters from a single input image. Unlike other methods, our network is suitable to create high resolution output as it directly estimates the parameters from the image which then can be used to rectify even very high resolution input images. As our method it is fully automatic, it is suitable for both casual creatives and professional artists. Our results show that our network accurately predicts the lens distortion parameters of high resolution images and corrects the distortions satisfactory.en
dc.language.isoenen
dc.rightsYen
dc.subjectCamera calibrationen
dc.subjectLens distortionen
dc.subjectCNNen
dc.subjectDeep learningen
dc.subjectConvolutional neural networksen
dc.titleDeep Convolutional Neural Networks for estimating lens distortion parametersen
dc.title.alternativeIrish Machine Vision and Image Processing Conference (IMVIP) 2019, 2019.en
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/smolica
dc.identifier.rssinternalid212582
dc.identifier.doihttps://doi.org/10.25546/91573
dc.rights.ecaccessrightsopenAccess
dc.subject.TCDThemeCreative Technologiesen
dc.subject.TCDTagMultimedia & Creativityen
dc.subject.darat_impairmentOtheren
dc.status.accessibleNen
dc.contributor.sponsorSFI stipenden
dc.contributor.sponsorGrantNumber15/RP/2776en
dc.identifier.urihttps://v-sense.scss.tcd.ie/wp-content/uploads/2019/08/IMVIP___Lens_distortion1.pdf
dc.identifier.urihttp://hdl.handle.net/2262/91573


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