A visual guidance calibration method for out-of-focus cameras based on iterative phase target

Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of c...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Cao, Jianbin [verfasserIn] Zhang, Xu [verfasserIn] Tu, Dawei [verfasserIn] Zhou, Guangya [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance

Übergeordnetes Werk:	Enthalten in: Measurement - Amsterdam [u.a.] : Elsevier Science, 1983, 218
Übergeordnetes Werk:	volume:218

DOI / URN:	10.1016/j.measurement.2023.113104

Katalog-ID:	ELV060450304

Internformat


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245	1	0	\|a A visual guidance calibration method for out-of-focus cameras based on iterative phase target
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520			\|a Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration.
650		4	\|a Camera calibration
650		4	\|a Defocus camera
650		4	\|a Phase target
650		4	\|a Iterative-Gaussian
650		4	\|a Visual guidance
700	1		\|a Zhang, Xu \|e verfasserin \|4 aut
700	1		\|a Tu, Dawei \|e verfasserin \|4 aut
700	1		\|a Zhou, Guangya \|e verfasserin \|4 aut
773	0	8	\|i Enthalten in \|t Measurement \|d Amsterdam [u.a.] : Elsevier Science, 1983 \|g 218 \|h Online-Ressource \|w (DE-627)320404927 \|w (DE-600)2000550-7 \|w (DE-576)259484342 \|7 nnns
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912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
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912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
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912			\|a GBV_ILN_4242
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912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
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936	b	k	\|a 50.21 \|j Messtechnik \|q VZ
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bklnumber	50.21
publishDate	2023
allfields	10.1016/j.measurement.2023.113104 doi (DE-627)ELV060450304 (ELSEVIER)S0263-2241(23)00668-1 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Cao, Jianbin verfasserin (orcid)0000-0001-5909-4118 aut A visual guidance calibration method for out-of-focus cameras based on iterative phase target 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration. Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance Zhang, Xu verfasserin aut Tu, Dawei verfasserin aut Zhou, Guangya verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 218 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:218 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 218
spelling	10.1016/j.measurement.2023.113104 doi (DE-627)ELV060450304 (ELSEVIER)S0263-2241(23)00668-1 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Cao, Jianbin verfasserin (orcid)0000-0001-5909-4118 aut A visual guidance calibration method for out-of-focus cameras based on iterative phase target 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration. Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance Zhang, Xu verfasserin aut Tu, Dawei verfasserin aut Zhou, Guangya verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 218 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:218 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 218
allfields_unstemmed	10.1016/j.measurement.2023.113104 doi (DE-627)ELV060450304 (ELSEVIER)S0263-2241(23)00668-1 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Cao, Jianbin verfasserin (orcid)0000-0001-5909-4118 aut A visual guidance calibration method for out-of-focus cameras based on iterative phase target 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration. Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance Zhang, Xu verfasserin aut Tu, Dawei verfasserin aut Zhou, Guangya verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 218 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:218 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 218
allfieldsGer	10.1016/j.measurement.2023.113104 doi (DE-627)ELV060450304 (ELSEVIER)S0263-2241(23)00668-1 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Cao, Jianbin verfasserin (orcid)0000-0001-5909-4118 aut A visual guidance calibration method for out-of-focus cameras based on iterative phase target 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration. Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance Zhang, Xu verfasserin aut Tu, Dawei verfasserin aut Zhou, Guangya verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 218 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:218 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 218
allfieldsSound	10.1016/j.measurement.2023.113104 doi (DE-627)ELV060450304 (ELSEVIER)S0263-2241(23)00668-1 DE-627 ger DE-627 rda eng 660 VZ 50.21 bkl Cao, Jianbin verfasserin (orcid)0000-0001-5909-4118 aut A visual guidance calibration method for out-of-focus cameras based on iterative phase target 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration. Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance Zhang, Xu verfasserin aut Tu, Dawei verfasserin aut Zhou, Guangya verfasserin aut Enthalten in Measurement Amsterdam [u.a.] : Elsevier Science, 1983 218 Online-Ressource (DE-627)320404927 (DE-600)2000550-7 (DE-576)259484342 nnns volume:218 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 50.21 Messtechnik VZ AR 218
language	English
source	Enthalten in Measurement 218 volume:218
sourceStr	Enthalten in Measurement 218 volume:218
format_phy_str_mv	Article
bklname	Messtechnik
institution	findex.gbv.de
topic_facet	Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance
dewey-raw	660
isfreeaccess_bool	false
container_title	Measurement
authorswithroles_txt_mv	Cao, Jianbin @@aut@@ Zhang, Xu @@aut@@ Tu, Dawei @@aut@@ Zhou, Guangya @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320404927
dewey-sort	3660
id	ELV060450304
language_de	englisch
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author	Cao, Jianbin
spellingShingle	Cao, Jianbin ddc 660 bkl 50.21 misc Camera calibration misc Defocus camera misc Phase target misc Iterative-Gaussian misc Visual guidance A visual guidance calibration method for out-of-focus cameras based on iterative phase target
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topic_title	660 VZ 50.21 bkl A visual guidance calibration method for out-of-focus cameras based on iterative phase target Camera calibration Defocus camera Phase target Iterative-Gaussian Visual guidance
topic	ddc 660 bkl 50.21 misc Camera calibration misc Defocus camera misc Phase target misc Iterative-Gaussian misc Visual guidance
topic_unstemmed	ddc 660 bkl 50.21 misc Camera calibration misc Defocus camera misc Phase target misc Iterative-Gaussian misc Visual guidance
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title	A visual guidance calibration method for out-of-focus cameras based on iterative phase target
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title_full	A visual guidance calibration method for out-of-focus cameras based on iterative phase target
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author_browse	Cao, Jianbin Zhang, Xu Tu, Dawei Zhou, Guangya
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title_sort	a visual guidance calibration method for out-of-focus cameras based on iterative phase target
title_auth	A visual guidance calibration method for out-of-focus cameras based on iterative phase target
abstract	Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration.
abstractGer	Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration.
abstract_unstemmed	Calibration of out-of-focus cameras is crucial for some special 3d reconstruction applications. An essential factor in improving the calibration result is avoiding the solution's singularity which tends to pose the calibration plate at a large inclination. However, the depth of field (DOF) of cameras is limited, especially in the defocused scenes, and the blurred corners will significantly reduce the calibration accuracy. A vision-guided calibration method is proposed, including an optimal pose selection algorithm and an iterative phase-target technology. Compared with other phase-target methods, this method simultaneously optimizes the mathematical properties of the solution and the angular uncertainty of the corners. Compared with the Chessboard-target or Circle-target, this method has a higher calibration accuracy at three different distances that gradually change from focusing to defocusing. In addition, experiments also prove the effectiveness of the two submodules: Gaussian iteration and vision guidance. Finally, its code is available in the URL: https://github.com/SHU-FLYMAN/Visual-Guidence-Calibration.
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title_short	A visual guidance calibration method for out-of-focus cameras based on iterative phase target
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author2	Zhang, Xu Tu, Dawei Zhou, Guangya
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doi_str	10.1016/j.measurement.2023.113104
up_date	2024-07-06T23:53:56.220Z
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A visual guidance calibration method for out-of-focus cameras based on iterative phase target

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