000077264 001__ 77264
000077264 005__ 20191212100659.0
000077264 0247_ $$2doi$$a10.1016/j.cviu.2018.01.003
000077264 0248_ $$2sideral$$a104898
000077264 037__ $$aART-2018-104898
000077264 041__ $$aeng
000077264 100__ $$0(orcid)0000-0002-8479-1748$$aBermúdez-Cameo, Jesús$$uUniversidad de Zaragoza
000077264 245__ $$aFitting line projections in non-central catadioptric cameras with revolution symmetry
000077264 260__ $$c2018
000077264 5060_ $$aAccess copy available to the general public$$fUnrestricted
000077264 5203_ $$aLine-images in non-central cameras contain much richer information of the original 3D line than line projections in central cameras. The projection surface of a 3D line in most catadioptric non-central cameras is a ruled surface, encapsulating the complete information of the 3D line. The resulting line-image is a curve which contains the 4 degrees of freedom of the 3D line. That means a qualitative advantage with respect to the central case, although extracting this curve is quite difficult. In this paper, we focus on the analytical description of the line-images in non-central catadioptric systems with symmetry of revolution. As a direct application we present a method for automatic line-image extraction for conical and spherical calibrated catadioptric cameras. For designing this method we have analytically solved the metric distance from point to line-image for non-central catadioptric systems. We also propose a distance we call effective baseline measuring the quality of the reconstruction of a 3D line from the minimum number of rays. This measure is used to evaluate the different random attempts of a robust scheme allowing to reduce the number of trials in the process. The proposal is tested and evaluated in simulations and with both synthetic and real images.
000077264 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/DPI2014-61792-EXP$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2015-65962-R
000077264 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000077264 590__ $$a2.645$$b2018
000077264 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b115 / 265 = 0.434$$c2018$$dQ2$$eT2
000077264 591__ $$aCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE$$b58 / 133 = 0.436$$c2018$$dQ2$$eT2
000077264 592__ $$a0.766$$b2018
000077264 593__ $$aComputer Vision and Pattern Recognition$$c2018$$dQ1
000077264 593__ $$aSoftware$$c2018$$dQ1
000077264 593__ $$aSignal Processing$$c2018$$dQ1
000077264 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000077264 700__ $$0(orcid)0000-0001-9347-5969$$aLópez-Nicolás, Gonzalo$$uUniversidad de Zaragoza
000077264 700__ $$0(orcid)0000-0001-5209-2267$$aGuerrero, José J.$$uUniversidad de Zaragoza
000077264 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000077264 773__ $$g167 (2018), 134-152$$pComput. vis. image underst.$$tCOMPUTER VISION AND IMAGE UNDERSTANDING$$x1077-3142
000077264 8564_ $$s4159449$$uhttps://zaguan.unizar.es/record/77264/files/texto_completo.pdf$$yPostprint
000077264 8564_ $$s90720$$uhttps://zaguan.unizar.es/record/77264/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000077264 909CO $$ooai:zaguan.unizar.es:77264$$particulos$$pdriver
000077264 951__ $$a2019-12-12-10:03:15
000077264 980__ $$aARTICLE