Method for large-scale structured-light system calibration
We propose a multi-stage calibration method for increasing the overall accuracy of a large-scale structured light system by leveraging the conventional stereo calibration approach using a pinhole model. We first calibrate the intrinsic parameters at a near distance and then the extrinsic parameters...
- Autores:
-
Marrugo Hernández, Andrés Guillermo
Vargas, Raúl
Romero, Lenny A
Zhang, Song
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/10352
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/10352
- Palabra clave:
- Image reconstruction
Pixels
Calibration method
Calibration targets
Extrinsic parameter
Intrinsic parameters
Low-order polynomials
Polynomial functions
Stereo calibration
Structured light systems
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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| dc.title.spa.fl_str_mv |
Method for large-scale structured-light system calibration |
| title |
Method for large-scale structured-light system calibration |
| spellingShingle |
Method for large-scale structured-light system calibration Image reconstruction Pixels Calibration method Calibration targets Extrinsic parameter Intrinsic parameters Low-order polynomials Polynomial functions Stereo calibration Structured light systems LEMB |
| title_short |
Method for large-scale structured-light system calibration |
| title_full |
Method for large-scale structured-light system calibration |
| title_fullStr |
Method for large-scale structured-light system calibration |
| title_full_unstemmed |
Method for large-scale structured-light system calibration |
| title_sort |
Method for large-scale structured-light system calibration |
| dc.creator.fl_str_mv |
Marrugo Hernández, Andrés Guillermo Vargas, Raúl Romero, Lenny A Zhang, Song |
| dc.contributor.author.none.fl_str_mv |
Marrugo Hernández, Andrés Guillermo Vargas, Raúl Romero, Lenny A Zhang, Song |
| dc.subject.keywords.spa.fl_str_mv |
Image reconstruction Pixels Calibration method Calibration targets Extrinsic parameter Intrinsic parameters Low-order polynomials Polynomial functions Stereo calibration Structured light systems |
| topic |
Image reconstruction Pixels Calibration method Calibration targets Extrinsic parameter Intrinsic parameters Low-order polynomials Polynomial functions Stereo calibration Structured light systems LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
We propose a multi-stage calibration method for increasing the overall accuracy of a large-scale structured light system by leveraging the conventional stereo calibration approach using a pinhole model. We first calibrate the intrinsic parameters at a near distance and then the extrinsic parameters with a low-cost large-calibration target at the designed measurement distance. Finally, we estimate pixel-wise errors from standard stereo 3D reconstructions and determine the pixel-wise phase-to-coordinate relationships using low-order polynomials. The calibrated pixel-wise polynomial functions can be used for 3D reconstruction for a given pixel phase value. We experimentally demonstrated that our proposed method achieves high accuracy for a large volume: sub-millimeter within 1200(H) × 800 (V) × 1000(D) mm3 . |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2021-08-03T19:16:52Z |
| dc.date.available.none.fl_str_mv |
2021-08-03T19:16:52Z |
| dc.date.issued.none.fl_str_mv |
2021-05-24 |
| dc.date.submitted.none.fl_str_mv |
2021-08-03 |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
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info:eu-repo/semantics/restrictedAccess |
| dc.type.spa.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.identifier.citation.spa.fl_str_mv |
Andres G. Marrugo, Raul Vargas, Lenny A. Romero, and Song Zhang, "Method for large-scale structured-light system calibration," Opt. Express 29, 17316-17329 (2021) |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10352 |
| dc.identifier.doi.none.fl_str_mv |
10.1364/OE.422327 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Andres G. Marrugo, Raul Vargas, Lenny A. Romero, and Song Zhang, "Method for large-scale structured-light system calibration," Opt. Express 29, 17316-17329 (2021) 10.1364/OE.422327 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/10352 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
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14 páginas |
| dc.coverage.spatial.none.fl_str_mv |
Colombia |
| dc.publisher.place.spa.fl_str_mv |
Cartagena de Indias |
| dc.source.spa.fl_str_mv |
Optics Express Vol. 29, No. 11 / 24 May 2021 |
| institution |
Universidad Tecnológica de Bolívar |
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Marrugo Hernández, Andrés Guillermo202eb167-fa09-441e-a322-6ec0f49ce713Vargas, Raúl7ed74a59-2212-4695-92fb-306ef719f47dRomero, Lenny A4e34aa8a-f981-4e1d-ae32-d45acb6abcf9Zhang, Song21575f5c-6086-4494-bdc6-f08c810268d2Colombia2021-08-03T19:16:52Z2021-08-03T19:16:52Z2021-05-242021-08-03Andres G. Marrugo, Raul Vargas, Lenny A. Romero, and Song Zhang, "Method for large-scale structured-light system calibration," Opt. Express 29, 17316-17329 (2021)https://hdl.handle.net/20.500.12585/1035210.1364/OE.422327Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarWe propose a multi-stage calibration method for increasing the overall accuracy of a large-scale structured light system by leveraging the conventional stereo calibration approach using a pinhole model. We first calibrate the intrinsic parameters at a near distance and then the extrinsic parameters with a low-cost large-calibration target at the designed measurement distance. Finally, we estimate pixel-wise errors from standard stereo 3D reconstructions and determine the pixel-wise phase-to-coordinate relationships using low-order polynomials. The calibrated pixel-wise polynomial functions can be used for 3D reconstruction for a given pixel phase value. We experimentally demonstrated that our proposed method achieves high accuracy for a large volume: sub-millimeter within 1200(H) × 800 (V) × 1000(D) mm3 .application/pdf14 páginasenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Optics Express Vol. 29, No. 11 / 24 May 2021Method for large-scale structured-light system calibrationinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_2df8fbb1Image reconstructionPixelsCalibration methodCalibration targetsExtrinsic parameterIntrinsic parametersLow-order polynomialsPolynomial functionsStereo calibrationStructured light systemsLEMBCartagena de IndiasInvestigadoresT. Bell, J. Xu, and S. Zhang, “Method for out-of-focus camera calibration,” Appl. Opt. 55(9), 2346–2352 (2016)B. Li, N. Karpinsky, and S. Zhang, “Novel calibration method for structured-light system with an out-of-focus projector,” Appl. Opt. 53(16), 3415–3426 (2014).Y. An, T. Bell, B. Li, J. Xu, and S. Zhang, “Method for large-range structured light system calibration,” Appl. Opt. 55(33), 9563–9572 (2016)S. Yang, M. Liu, J. Song, S. Yin, Y. Ren, J. Zhu, and S. Chen, “Projector distortion residual compensation in fringe projection system,” Opt. Lasers Eng. 114, 104–110 (2019). S. Lv, Q. Sun, Y. Zhang, Y. Jiang, J. Yang, J. Liu, and J. Wang, “Projector distortion correction in 3D shape measurement using a structured-light system by deep neural networks,” Opt. Lett. 45(1), 204–207 (2020).. J. Villa, M. Araiza, D. Alaniz, R. Ivanov, and M. Ortiz, “Transformation of phase to (x, y, z)-coordinates for the calibration of a fringe projection profilometer,” Opt. Lasers Eng. 50(2), 256–261 (2012).R. Vargas, A. G. Marrugo, J. Pineda, J. Meneses, and L. A. Romero, “Camera-Projector Calibration Methods with Compensation of Geometric Distortions in Fringe Projection Profilometry: A Comparative Study,” Opt. Pura Apl. 51(3), 1–10 (2018)A. G. Marrugo, F. Gao, and S. Zhang, “State-of-the-art active optical techniques for three-dimensional surface metrology: a review,” J. Opt. Soc. Am. A 37(9), B60–B77 (2020).S. Gai, F. Da, and M. Tang, “A flexible multi-view calibration and 3d measurement method based on digital fringe projection,” Meas. Sci. Technol. 30(2), 025203 (2019).. S. Yin, Y. Ren, Y. Guo, J. Zhu, S. Yang, and S. Ye, “Development and calibration of an integrated 3D scanning system for high-accuracy large-scale metrology,” Measurement 54, 65–76 (2014).. I. Léandry, C. Bréque, and V. Valle, “Calibration of a structured-light projection system: Development to large dimension objects,” Opt. Lasers Eng. 50(3), 373–379 (2012).P. Wang, J. Wang, J. Xu, Y. Guan, G. Zhang, and K. Chen, “Calibration method for a large-scale structured light measurement system,” Appl. Opt. 56(14), 3995–4002 (2017). X. Liu, Z. Cai, Y. Yin, H. Jiang, D. He, W. He, Z. Zhang, and X. Peng, “Calibration of fringe projection profilometry using an inaccurate 2D reference target,” Opt. Lasers Eng. 89, 131–137 (2017).. J. Yu and F. Da, “Calibration refinement for a fringe projection profilometry system based on plane homography,” Opt. Lasers Eng. 140, 106525 (2021).S. Xing and H. Guo, “Iterative calibration method for measurement system having lens distortions in fringe projection profilometry,” Opt. Express 28(2), 1177–1196 (2020).. R. Vargas, A. G. Marrugo, S. Zhang, and L. A. Romero, “Hybrid calibration procedure for fringe projection profilometry based on stereo vision and polynomial fitting,” Appl. Opt. 59(13), D163–D169 (2020).S. Zhang and P. S. Huang, “Novel method for structured light system calibration,” Opt. Eng. 45(8), 083601 (2006)8. S. Zhang, High-Speed 3D Imaging with Digital Fringe Projection Techniques (CRC Press, 2016). K. Li, J. Bu, and D. Zhang, “Lens distortion elimination for improving measurement accuracy of fringe projection profilometry,” Opt. Lasers Eng. 85, 53–64 (2016).Z. Zhang, “A Flexible New Technique for Camera Calibration,” IEEE Trans. Pattern Anal. Machine Intell. 22(11), 1330–1334 (2000).R. Juarez-Salazar, A. Giron, J. Zheng, and V. H. Diaz-Ramirez, “Key concepts for phase-to-coordinate conversion in fringe projection systems,” Appl. Opt. 58(18), 4828–4834 (2019).A. G. Marrugo, R. Vargas, S. Zhang, and L. A. Romero, “Hybrid calibration method for improving 3D measurement accuracy of structured light systems,” Proc. SPIE 11490, 1149008 (2020).. J. M. Lavest, M. Viala, and M. Dhome, “Do we really need an accurate calibration pattern to achieve a reliable camera calibration?” in Computer Vision — ECCV’98, (Springer, Berlin, Heidelberg, Berlin, Heidelberg, 1998), pp. 158–174L. Huang, Q. Zhang, and A. Asundi, “Camera calibration with active phase target: improvement on feature detection and optimization,” Opt. Lett. 38(9), 1446–1448 (2013).X.-L. Zhang, B.-F. Zhang, and Y.-C. Lin, “Accurate phase expansion on reference planes in grating projection profilometry,” Meas. Sci. 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