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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)ORCID iD: 0000-0003-3751-6089
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, Published 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: 2018-01-10Bibliographically approved

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AssessmentOfMultiCameraCalibrationAlgorithms(496 kB)241 downloads
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Dima, ElijsSjöström, MårtenOlsson, Roger

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