Complete camera calibration using line-shape objects

He, X; Zhang, H; Hur, N; Kim, J; Kim, T; Wu, Q

Complete camera calibration using line-shape objects

He, X

Zhang, H Hur, N Kim, J Kim, T Wu, Q

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Publication Type:: Conference Proceeding
Citation:: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2006
Issue Date:: 2006-01-01

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Field	Value	Language
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Zhang, H	en_US
dc.contributor.author	Hur, N	en_US
dc.contributor.author	Kim, J	en_US
dc.contributor.author	Kim, T	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.date.issued	2006-01-01	en_US
dc.identifier.citation	IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2006	en_US
dc.identifier.isbn	1424405491	en_US
dc.identifier.isbn	9781424405497	en_US
dc.identifier.issn	2159-3442	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2565
dc.description.abstract	Most of object-based calibration methods used 3D or 2D pattern. A novel and more flexible 1D object-based calibration was introduced only a couple of years ago, and merely for estimation of intrinsic parameters without consideration camera distortion. Estimation of extrinsic papers is essential when multiple cameras are involved for simultaneously taking images from different view angles and when the knowledge of relative locations between the cameras is required. Estimation of distortion parameters is critical for precise estimation of all calibration parameters. In this paper, we will perform a multi-layer camera calibration involving both intrinsic and extrinsic parameters including distortion parameters based on a line-shape calibration object. © 2006 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0451666
dc.relation.ispartof	IEEE Region 10 Annual International Conference, Proceedings/TENCON	en_US
dc.relation.isbasedon	10.1109/TENCON.2006.344175	en_US
dc.title	Complete camera calibration using line-shape objects	en_US
dc.type	Conference Proceeding
utslib.for	080106 Image Processing	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Honk Kong, China	en_US
dc.location.activity	Changmai, Thailand
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Most of object-based calibration methods used 3D or 2D pattern. A novel and more flexible 1D object-based calibration was introduced only a couple of years ago, and merely for estimation of intrinsic parameters without consideration camera distortion. Estimation of extrinsic papers is essential when multiple cameras are involved for simultaneously taking images from different view angles and when the knowledge of relative locations between the cameras is required. Estimation of distortion parameters is critical for precise estimation of all calibration parameters. In this paper, we will perform a multi-layer camera calibration involving both intrinsic and extrinsic parameters including distortion parameters based on a line-shape calibration object. © 2006 IEEE.

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http://hdl.handle.net/10453/2565