Calibration of an Outdoor Distributed Camera Network with a 3D Point Cloud

Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tas...

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Published inSensors (Basel, Switzerland) Vol. 14; no. 8; pp. 13708 - 13729
Main Authors Ortega, Agustín, Silva, Manuel, Teniente, Ernesto, Ferreira, Ricardo, Bernardino, Alexandre, Gaspar, José, Andrade-Cetto, Juan
Format Journal Article Publication
LanguageEnglish
Published Switzerland MDPI AG 29.07.2014
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Abstract Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).
AbstractList Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).
Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matematiques i Estadistica (FME) patio at the Universitat Politecnica de Catalunya (UPC).
Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).
Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matematiques i Estadistica (FME) patio at the Universitat Politecnica de Catalunya (UPC). Peer Reviewed
Author Ortega, Agustín
Silva, Manuel
Andrade-Cetto, Juan
Ferreira, Ricardo
Teniente, Ernesto
Bernardino, Alexandre
Gaspar, José
AuthorAffiliation 1 Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens Artigas 4-6, Barcelona 08028, Spain; E-Mail: ehomar@iri.upc.edu
2 Institute for Systems and Robotics, Instituto Superior Técnico, Av. Rovisco Pais 1, Lisbon 1049-001, Portugal; E-Mails: manuel.silva.thesis@gmail.com (M.S.); ricardo@isr.ist.utl.pt (R.F.); alex@isr.ist.utl.pt (A.B.); jag@isr.ist.utl.pt (J.G.)
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CitedBy_id crossref_primary_10_1016_j_cviu_2015_05_015
crossref_primary_10_3390_biomimetics9090560
crossref_primary_10_1016_j_adhoc_2019_01_007
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Snippet Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera...
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StartPage 13708
SubjectTerms Algorithms
Artificial Intelligence
Automation
Automàtica i control
Calibration
camera network calibration
Cameras
Classificació INSPEC
ENVIRONMENTS
Image Interpretation, Computer-Assisted - instrumentation
Image Interpretation, Computer-Assisted - methods
Imaging, Three-Dimensional - instrumentation
Imaging, Three-Dimensional - methods
Informàtica
Lasers
Networks
Optimization techniques
Outdoor
Pattern Recognition, Automated - methods
Robots
Sensors
Three dimensional
Three dimensional models
Urban areas
Àrees temàtiques de la UPC
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Title Calibration of an Outdoor Distributed Camera Network with a 3D Point Cloud
URI https://www.ncbi.nlm.nih.gov/pubmed/25076221
https://www.proquest.com/docview/1561832181
https://www.proquest.com/docview/1551021242
https://www.proquest.com/docview/1566834150
https://www.proquest.com/docview/1651378652
https://recercat.cat/handle/2072/249667
https://pubmed.ncbi.nlm.nih.gov/PMC4179065
https://doaj.org/article/3bfca61bd84a4720887f53b1ac560c87
Volume 14
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