A monocular wide-field vision system for geolocation with uncertainties in urban scenes

Autores
Arroyo, Sebastián Ismael; Bussi, Ulises; Safar, Felix Gustavo Emilio; Oliva, Damian Ernesto
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In engineering applications related to video surveillance, the use of monocular omnidirectional cameras would reduce costs and complications associated with infrastructure, installation, synchronization, maintenance and operation of multiple cameras. This makes omnidirectional cameras very useful for transport analysis, a key task of which is to accurately geolocate vehicles and/or pedestrians observed in an ample region. The problem of measuring on the plane was previously solved for monocular central perspective images. However, the problem of determining uncertainties in geolocalization using monocular omnidirectional images, has not been addressed. This problem is not trivial due to the complexity of the image formation models associated with these cameras. The contributions of this work are: (1) The geolocation problem is solved using omnidirectional monocular images through a Bayesian inference approach. (2) The calculation of Bayesian marginalization integrals is simplified through first-order approximations. (3) The accuracy of the estimated positions and uncertainties is shown through Monte Carlo simulations under realistic measurement conditions. (4) The method to geolocate a vehicle´s trajectory on a satellite map is applied in an urban setting.
Fil: Arroyo, Sebastián Ismael. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Fil: Bussi, Ulises. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Safar, Felix Gustavo Emilio. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Fil: Oliva, Damian Ernesto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Materia
OMNIDIRECTIONAL VISION
FISHEYE
COMPUTER VISION
CAMERA CALIBRATION
BAYESIAN INFERENCE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/155907

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spelling A monocular wide-field vision system for geolocation with uncertainties in urban scenesArroyo, Sebastián IsmaelBussi, UlisesSafar, Felix Gustavo EmilioOliva, Damian ErnestoOMNIDIRECTIONAL VISIONFISHEYECOMPUTER VISIONCAMERA CALIBRATIONBAYESIAN INFERENCEhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In engineering applications related to video surveillance, the use of monocular omnidirectional cameras would reduce costs and complications associated with infrastructure, installation, synchronization, maintenance and operation of multiple cameras. This makes omnidirectional cameras very useful for transport analysis, a key task of which is to accurately geolocate vehicles and/or pedestrians observed in an ample region. The problem of measuring on the plane was previously solved for monocular central perspective images. However, the problem of determining uncertainties in geolocalization using monocular omnidirectional images, has not been addressed. This problem is not trivial due to the complexity of the image formation models associated with these cameras. The contributions of this work are: (1) The geolocation problem is solved using omnidirectional monocular images through a Bayesian inference approach. (2) The calculation of Bayesian marginalization integrals is simplified through first-order approximations. (3) The accuracy of the estimated positions and uncertainties is shown through Monte Carlo simulations under realistic measurement conditions. (4) The method to geolocate a vehicle´s trajectory on a satellite map is applied in an urban setting.Fil: Arroyo, Sebastián Ismael. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Bussi, Ulises. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Safar, Felix Gustavo Emilio. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Oliva, Damian Ernesto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaIOP Publishing2020-06-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/155907Arroyo, Sebastián Ismael; Bussi, Ulises; Safar, Felix Gustavo Emilio; Oliva, Damian Ernesto; A monocular wide-field vision system for geolocation with uncertainties in urban scenes; IOP Publishing; Engineering Research Express; 2; 2; 22-6-2020; 1-192631-8695CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1088/2631-8695/ab9b36info:eu-repo/semantics/altIdentifier/url/https://iopscience.iop.org/article/10.1088/2631-8695/ab9b36info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:37:34Zoai:ri.conicet.gov.ar:11336/155907instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:37:34.886CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A monocular wide-field vision system for geolocation with uncertainties in urban scenes
title A monocular wide-field vision system for geolocation with uncertainties in urban scenes
spellingShingle A monocular wide-field vision system for geolocation with uncertainties in urban scenes
Arroyo, Sebastián Ismael
OMNIDIRECTIONAL VISION
FISHEYE
COMPUTER VISION
CAMERA CALIBRATION
BAYESIAN INFERENCE
title_short A monocular wide-field vision system for geolocation with uncertainties in urban scenes
title_full A monocular wide-field vision system for geolocation with uncertainties in urban scenes
title_fullStr A monocular wide-field vision system for geolocation with uncertainties in urban scenes
title_full_unstemmed A monocular wide-field vision system for geolocation with uncertainties in urban scenes
title_sort A monocular wide-field vision system for geolocation with uncertainties in urban scenes
dc.creator.none.fl_str_mv Arroyo, Sebastián Ismael
Bussi, Ulises
Safar, Felix Gustavo Emilio
Oliva, Damian Ernesto
author Arroyo, Sebastián Ismael
author_facet Arroyo, Sebastián Ismael
Bussi, Ulises
Safar, Felix Gustavo Emilio
Oliva, Damian Ernesto
author_role author
author2 Bussi, Ulises
Safar, Felix Gustavo Emilio
Oliva, Damian Ernesto
author2_role author
author
author
dc.subject.none.fl_str_mv OMNIDIRECTIONAL VISION
FISHEYE
COMPUTER VISION
CAMERA CALIBRATION
BAYESIAN INFERENCE
topic OMNIDIRECTIONAL VISION
FISHEYE
COMPUTER VISION
CAMERA CALIBRATION
BAYESIAN INFERENCE
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In engineering applications related to video surveillance, the use of monocular omnidirectional cameras would reduce costs and complications associated with infrastructure, installation, synchronization, maintenance and operation of multiple cameras. This makes omnidirectional cameras very useful for transport analysis, a key task of which is to accurately geolocate vehicles and/or pedestrians observed in an ample region. The problem of measuring on the plane was previously solved for monocular central perspective images. However, the problem of determining uncertainties in geolocalization using monocular omnidirectional images, has not been addressed. This problem is not trivial due to the complexity of the image formation models associated with these cameras. The contributions of this work are: (1) The geolocation problem is solved using omnidirectional monocular images through a Bayesian inference approach. (2) The calculation of Bayesian marginalization integrals is simplified through first-order approximations. (3) The accuracy of the estimated positions and uncertainties is shown through Monte Carlo simulations under realistic measurement conditions. (4) The method to geolocate a vehicle´s trajectory on a satellite map is applied in an urban setting.
Fil: Arroyo, Sebastián Ismael. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Fil: Bussi, Ulises. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Safar, Felix Gustavo Emilio. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
Fil: Oliva, Damian Ernesto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina
description In engineering applications related to video surveillance, the use of monocular omnidirectional cameras would reduce costs and complications associated with infrastructure, installation, synchronization, maintenance and operation of multiple cameras. This makes omnidirectional cameras very useful for transport analysis, a key task of which is to accurately geolocate vehicles and/or pedestrians observed in an ample region. The problem of measuring on the plane was previously solved for monocular central perspective images. However, the problem of determining uncertainties in geolocalization using monocular omnidirectional images, has not been addressed. This problem is not trivial due to the complexity of the image formation models associated with these cameras. The contributions of this work are: (1) The geolocation problem is solved using omnidirectional monocular images through a Bayesian inference approach. (2) The calculation of Bayesian marginalization integrals is simplified through first-order approximations. (3) The accuracy of the estimated positions and uncertainties is shown through Monte Carlo simulations under realistic measurement conditions. (4) The method to geolocate a vehicle´s trajectory on a satellite map is applied in an urban setting.
publishDate 2020
dc.date.none.fl_str_mv 2020-06-22
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/155907
Arroyo, Sebastián Ismael; Bussi, Ulises; Safar, Felix Gustavo Emilio; Oliva, Damian Ernesto; A monocular wide-field vision system for geolocation with uncertainties in urban scenes; IOP Publishing; Engineering Research Express; 2; 2; 22-6-2020; 1-19
2631-8695
CONICET Digital
CONICET
url http://hdl.handle.net/11336/155907
identifier_str_mv Arroyo, Sebastián Ismael; Bussi, Ulises; Safar, Felix Gustavo Emilio; Oliva, Damian Ernesto; A monocular wide-field vision system for geolocation with uncertainties in urban scenes; IOP Publishing; Engineering Research Express; 2; 2; 22-6-2020; 1-19
2631-8695
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1088/2631-8695/ab9b36
info:eu-repo/semantics/altIdentifier/url/https://iopscience.iop.org/article/10.1088/2631-8695/ab9b36
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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