Zwierzak, I., Stoddart, D. orcid.org/0000-0002-8400-3190 and Hitchens, C. orcid.org/0000-0003-1093-0298 (2017) Imaging solutions for harsh environments. In: Procedia CIRP. 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering Elsevier BV , pp. 396-399.
Abstract
This paper presents a quantitative assessment of uncertainty for the stereo calibration at different cameras angle and control object 3D reconstruction. Stereo-photogrammetry with high resolution commercially available digital cameras is applied to deliver a 3D data from a pair of 2D images. The main goal of the project is the reconstruction of the 3D model from the images obtained underwater in a high vibration manufacturing environment. The crucial step in obtaining high accuracy 3D data is stereo-rig calibration. Robust camera calibration is a critical step in 3D reconstructions in order to extract precise quantitative measurements from 2D images. Two AV 6600 monochrome 29 Megapixels GigE cameras were calibrated at four different angles to ensure that the angle of the stereo rig and variation in image contrast would not influence significantly the final results. All the images were undertaken in the high vibration manufacturing environment. It was shown that calibration of the cameras set at the angle of 15o reduces significantly 3D reconstruction accuracy. However, it does not influence reprojection error, which is less than 0.5 pixels.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | photogrammetry; calibration; camera angles; vibration |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Advanced Manufacturing Institute (Sheffield) > Nuclear Advanced Manufacturing Research Centre |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Nov 2019 09:31 |
Last Modified: | 19 Nov 2019 09:37 |
Status: | Published online |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.procir.2016.07.081 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:153428 |