Estimation of camera calibration uncertainty using LIDAR data

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/22235

dc.contributor	Institut de Robòtica i Informàtica Industrial
dc.contributor	Universitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel.ligents
dc.contributor.author	Ortega Jimenez, Agustin Alberto
dc.contributor.author	Galego, Ricardo
dc.contributor.author	Ferreira, Ricardo
dc.contributor.author	Bernardino Bernardino Malheiro, Alexandre José
dc.contributor.author	Gaspar, José
dc.contributor.author	Andrade-Cetto, Juan
dc.date	2013
dc.identifier.citation	Ortega Jimenez, A. [et al.]. Estimation of camera calibration uncertainty using LIDAR data. A: European Conference on Mobile Robots. "Proceedings of the 6th European Conference on Mobile Robots". Barcelona: 2013, p. 361-366.
dc.identifier.citation	10.1109/ECMR.2013.6698868
dc.identifier.uri	http://hdl.handle.net/2117/22235
dc.language.iso	eng
dc.relation	http://dx.doi.org/10.1109/ECMR.2013.6698868
dc.relation	info:eu-repo/grantAgreement/EC/FP7/287617/EU/Aerial Robotics Cooperative Assembly System/ARCAS
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Informàtica::Robòtica
dc.subject	Computer vision
dc.subject	Robots
dc.subject	computer vision robots
dc.subject	Robòtica
dc.subject	Visió per ordinador
dc.subject	Classificació INSPEC::Automation::Robots
dc.subject	Classificació INSPEC::Pattern recognition::Computer vision
dc.title	Estimation of camera calibration uncertainty using LIDAR data
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	This paper presents an analysis of uncertainty in the calibration of a network of cameras. A global 3D scene model, acquired with a LIDAR scanner, allows calibrating cameras with non overlapping ¿elds of view by means of the DLT-Lines algorithm. Once the projection matrix is computed for each camera, error sources are propagated to compute estimates of each camera position uncertainty. We validate the consistency of the uncertainty analysis with Monte-Carlo simulations, and apply the technique in a real camera network. This allows to evaluate the accuracy of DLT-Lines in real settings.
dc.description.abstract	Peer Reviewed

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