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Assessment of Multi-Camera Calibration Algorithms for Two-Dimensional Camera Arrays Relative to Ground Truth Position and Direction
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)ORCID iD: 0000-0002-4967-3033
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. (Realistic3D)
2016 (English)In: 3DTV-Conference, IEEE Computer Society, 2016, 7548887Conference paper, (Refereed)
Abstract [en]

Camera calibration methods are commonly evaluated on cumulative reprojection error metrics, on disparate one-dimensional da-tasets. To evaluate calibration of cameras in two-dimensional arrays, assessments need to be made on two-dimensional datasets with constraints on camera parameters. In this study, accuracy of several multi-camera calibration methods has been evaluated on camera parameters that are affecting view projection the most. As input data, we used a 15-viewpoint two-dimensional dataset with intrinsic and extrinsic parameter constraints and extrinsic ground truth. The assessment showed that self-calibration methods using structure-from-motion reach equal intrinsic and extrinsic parameter estimation accuracy with standard checkerboard calibration algorithm, and surpass a well-known self-calibration toolbox, BlueCCal. These results show that self-calibration is a viable approach to calibrating two-dimensional camera arrays, but improvements to state-of-art multi-camera feature matching are necessary to make BlueCCal as accurate as other self-calibration methods for two-dimensional camera arrays.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016. 7548887
Keyword [en]
Camera calibration, multi-view image dataset, 2D camera array, self-calibration, calibration assessment
National Category
Signal Processing Media and Communication Technology
Identifiers
URN: urn:nbn:se:miun:diva-27960DOI: 10.1109/3DTV.2016.7548887ISI: 000390840500006Scopus ID: 2-s2.0-84987849952Local ID: STCISBN: 978-1-5090-3313-3 (print)OAI: oai:DiVA.org:miun-27960DiVA: diva2:938875
Conference
2016 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video, 3DTV-CON 2016; Hamburg; Germany; 4 July 2016 through 6 July 2016; Category numberCFP1655B-ART; Code 123582
Funder
Knowledge Foundation, 20140200
Available from: 2016-06-17 Created: 2016-06-16 Last updated: 2017-06-29Bibliographically approved

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AssessmentOfMultiCameraCalibrationAlgorithms(496 kB)179 downloads
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Dima, ElijsSjöström, MårtenOlsson, Roger
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
  • rtf