Publication:
Novel Bayesian Inference-Based Approach for the Uncertainty Characterization of Zhang's Camera Calibration Method

Simple item page
dc.affiliation.areaUC3M. Área de Ingeniería Mecánica
dc.affiliation.dptoUC3M. Departamento de Ingeniería Mecánica
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Advanced Vehicle Dynamics and Mechatronic Systems - VEDYMEC
dc.contributor.authorGutiérrez Moizant, Ramón Alberto
dc.contributor.authorLópez Boada, María Jesús
dc.contributor.authorRamírez Berasategui, María Beatriz
dc.contributor.authorAl Kaff, Abdulla Hussein Abdulrahman
dc.contributor.funderMinisterio de Ciencia e Innovación (España)es
dc.date.accessioned2023-10-09T11:58:47Z
dc.date.available2023-10-09T11:58:47Z
dc.date.issued2023-09-15
dc.description.abstractCamera calibration is necessary for many machine vision applications. The calibration methods are based on linear or non-linear optimization techniques that aim to find the best estimate of the camera parameters. One of the most commonly used methods in computer vision for the calibration of intrinsic camera parameters and lens distortion (interior orientation) is Zhang¿s method. Additionally, the uncertainty of the camera parameters is normally estimated by assuming that their variability can be explained by the images of the different poses of a checkerboard. However, the degree of reliability for both the best parameter values and their associated uncertainties has not yet been verified. Inaccurate estimates of intrinsic and extrinsic parameters during camera calibration may introduce additional biases in post-processing. This is why we propose a novel Bayesian inference-based approach that has allowed us to evaluate the degree of certainty of Zhang¿s camera calibration procedure. For this purpose, the a prioriprobability was assumed to be the one estimated by Zhang, and the intrinsic parameters were recalibrated by Bayesian inversion. The uncertainty of the intrinsic parameters was found to differ from the ones estimated with Zhang¿s method. However, the major source of inaccuracy is caused by the procedure for calculating the extrinsic parameters. The procedure used in the novel Bayesian inference-based approach significantly improves the reliability of the predictions of the image points, as it optimizes the extrinsic parameters.en
dc.description.sponsorshipThis work was supported by the Madrid Government (Comunidad de Madrid Spain) under the Multiannual Agreement with UC3M ("Fostering Young Doctors Research", APBI-CM-UC3M), and in the context of the VPRICIT (Research and Technological Innovation Regional Programme and by the FEDER/Ministry of Science and Innovation -Agencia Estatal de Investigacion (AEI) of the Government of Spain through the projects PID2022-136468OB-I00 and PID2022-142015OB-I00.en
dc.description.statusPublicadoes
dc.format.extent18
dc.identifier.bibliographicCitationSensors 2023, 23(18), 7903.en
dc.identifier.doihttps://doi.org/10.3390/s23187903
dc.identifier.issn1424-3210
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue18, 7903
dc.identifier.publicationlastpage18
dc.identifier.publicationtitleSensorsen
dc.identifier.publicationvolume23
dc.identifier.urihttps://hdl.handle.net/10016/38584
dc.identifier.uxxiAR/0000033372
dc.language.isoengen
dc.publisherMDPIen
dc.relation.projectIDGobierno de España. PID2022-136468OB-I00es
dc.relation.projectIDGobierno de España. PID2022-142015OB-I00es
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherCamera calibrationen
dc.subject.otherComputer visionen
dc.subject.otherUncertainty quantificationen
dc.subject.otherBayesian inversionen
dc.titleNovel Bayesian Inference-Based Approach for the Uncertainty Characterization of Zhang's Camera Calibration Methoden
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
novel_sensors_2023.pdf
Size:
601.63 KB
Format:
Adobe Portable Document Format
Download
Collections
DIM - MECATRAN - Artículos de revistas