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Conference Paper: A Screen-Based Method for Automated Camera Intrinsic Calibration on Production Lines
Title | A Screen-Based Method for Automated Camera Intrinsic Calibration on Production Lines |
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Authors | |
Keywords | Factory Automation Calibration and Identification Intelligent and Flexible Manufacturing |
Issue Date | 2019 |
Citation | 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), Vancouver, BC, Canada, 22-26 August 2019 How to Cite? |
Abstract | For the manufacture of visual system product, it is necessary to calibrate a massive number of cameras in a limited time and space with a high consistency quality. Traditional calibration method with chessboard pattern is not suitable in the manufacturing industry since its requirement of motions leads to the problem of consistency, cost of space and time. In this work, we present a screen-based solution for automated camera intrinsic calibration on production lines. With screens clearly and easily displaying pixel points, the whole calibration pattern is formed with the dense and uniform points captured by the camera. The calibration accuracy is comparable with the traditional method with chessboard pattern. Unlike a variety of existing methods, our method needs little human interaction, as well as only a limited amount of space, making it easy to be deployed and operated in the industrial environments. With some experiments, we show the comparable performance of the system for perspective cameras and its potential in fisheye cameras with the developments of screens. |
Description | FrCT4 Special Session: Data-Driven Operation Optimization of Smart Factories II - Paper FrCT4.6 |
Persistent Identifier | http://hdl.handle.net/10722/274462 |
DC Field | Value | Language |
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dc.contributor.author | Gao, W | - |
dc.contributor.author | Lin, J | - |
dc.contributor.author | Zhang, F | - |
dc.contributor.author | Shen, S | - |
dc.date.accessioned | 2019-08-18T15:02:11Z | - |
dc.date.available | 2019-08-18T15:02:11Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), Vancouver, BC, Canada, 22-26 August 2019 | - |
dc.identifier.uri | http://hdl.handle.net/10722/274462 | - |
dc.description | FrCT4 Special Session: Data-Driven Operation Optimization of Smart Factories II - Paper FrCT4.6 | - |
dc.description.abstract | For the manufacture of visual system product, it is necessary to calibrate a massive number of cameras in a limited time and space with a high consistency quality. Traditional calibration method with chessboard pattern is not suitable in the manufacturing industry since its requirement of motions leads to the problem of consistency, cost of space and time. In this work, we present a screen-based solution for automated camera intrinsic calibration on production lines. With screens clearly and easily displaying pixel points, the whole calibration pattern is formed with the dense and uniform points captured by the camera. The calibration accuracy is comparable with the traditional method with chessboard pattern. Unlike a variety of existing methods, our method needs little human interaction, as well as only a limited amount of space, making it easy to be deployed and operated in the industrial environments. With some experiments, we show the comparable performance of the system for perspective cameras and its potential in fisheye cameras with the developments of screens. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE 15th International Conference on Automation Science and Engineering (CASE) | - |
dc.subject | Factory Automation | - |
dc.subject | Calibration and Identification | - |
dc.subject | Intelligent and Flexible Manufacturing | - |
dc.title | A Screen-Based Method for Automated Camera Intrinsic Calibration on Production Lines | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Zhang, F: fuzhang@hku.hk | - |
dc.identifier.authority | Zhang, F=rp02460 | - |
dc.identifier.hkuros | 301107 | - |
dc.publisher.place | United States | - |