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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/155907
Ver los metadatos del registro completo
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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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1844614396165226496 |
score |
13.070432 |