High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC)
Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Huang, Mingyi [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Machine vision and applications - Berlin : Springer, 1988, 33(2022), 3 vom: 02. Apr. |
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| Übergeordnetes Werk: |
volume:33 ; year:2022 ; number:3 ; day:02 ; month:04 |
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| DOI / URN: |
10.1007/s00138-022-01296-9 |
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| Katalog-ID: |
SPR046655956 |
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| 520 | |a Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. | ||
| 650 | 4 | |a Fisheye lens calibration |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fisheye image correction |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Spherical projection |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Radial distortion projection ellipse constraint |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Wu, Jun |4 aut | |
| 700 | 1 | |a Zhiyong, Peng |4 aut | |
| 700 | 1 | |a Zhao, Xuemei |4 aut | |
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10.1007/s00138-022-01296-9 doi (DE-627)SPR046655956 (SPR)s00138-022-01296-9-e DE-627 ger DE-627 rakwb eng Huang, Mingyi verfasserin aut High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. Fisheye lens calibration (dpeaa)DE-He213 Fisheye image correction (dpeaa)DE-He213 Spherical projection (dpeaa)DE-He213 Radial distortion projection ellipse constraint (dpeaa)DE-He213 Wu, Jun aut Zhiyong, Peng aut Zhao, Xuemei aut Enthalten in Machine vision and applications Berlin : Springer, 1988 33(2022), 3 vom: 02. Apr. (DE-627)300186312 (DE-600)1481698-2 1432-1769 nnns volume:33 year:2022 number:3 day:02 month:04 https://dx.doi.org/10.1007/s00138-022-01296-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 3 02 04 |
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10.1007/s00138-022-01296-9 doi (DE-627)SPR046655956 (SPR)s00138-022-01296-9-e DE-627 ger DE-627 rakwb eng Huang, Mingyi verfasserin aut High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. Fisheye lens calibration (dpeaa)DE-He213 Fisheye image correction (dpeaa)DE-He213 Spherical projection (dpeaa)DE-He213 Radial distortion projection ellipse constraint (dpeaa)DE-He213 Wu, Jun aut Zhiyong, Peng aut Zhao, Xuemei aut Enthalten in Machine vision and applications Berlin : Springer, 1988 33(2022), 3 vom: 02. Apr. (DE-627)300186312 (DE-600)1481698-2 1432-1769 nnns volume:33 year:2022 number:3 day:02 month:04 https://dx.doi.org/10.1007/s00138-022-01296-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 3 02 04 |
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10.1007/s00138-022-01296-9 doi (DE-627)SPR046655956 (SPR)s00138-022-01296-9-e DE-627 ger DE-627 rakwb eng Huang, Mingyi verfasserin aut High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. Fisheye lens calibration (dpeaa)DE-He213 Fisheye image correction (dpeaa)DE-He213 Spherical projection (dpeaa)DE-He213 Radial distortion projection ellipse constraint (dpeaa)DE-He213 Wu, Jun aut Zhiyong, Peng aut Zhao, Xuemei aut Enthalten in Machine vision and applications Berlin : Springer, 1988 33(2022), 3 vom: 02. Apr. (DE-627)300186312 (DE-600)1481698-2 1432-1769 nnns volume:33 year:2022 number:3 day:02 month:04 https://dx.doi.org/10.1007/s00138-022-01296-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 3 02 04 |
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10.1007/s00138-022-01296-9 doi (DE-627)SPR046655956 (SPR)s00138-022-01296-9-e DE-627 ger DE-627 rakwb eng Huang, Mingyi verfasserin aut High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. Fisheye lens calibration (dpeaa)DE-He213 Fisheye image correction (dpeaa)DE-He213 Spherical projection (dpeaa)DE-He213 Radial distortion projection ellipse constraint (dpeaa)DE-He213 Wu, Jun aut Zhiyong, Peng aut Zhao, Xuemei aut Enthalten in Machine vision and applications Berlin : Springer, 1988 33(2022), 3 vom: 02. Apr. (DE-627)300186312 (DE-600)1481698-2 1432-1769 nnns volume:33 year:2022 number:3 day:02 month:04 https://dx.doi.org/10.1007/s00138-022-01296-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 3 02 04 |
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10.1007/s00138-022-01296-9 doi (DE-627)SPR046655956 (SPR)s00138-022-01296-9-e DE-627 ger DE-627 rakwb eng Huang, Mingyi verfasserin aut High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. Fisheye lens calibration (dpeaa)DE-He213 Fisheye image correction (dpeaa)DE-He213 Spherical projection (dpeaa)DE-He213 Radial distortion projection ellipse constraint (dpeaa)DE-He213 Wu, Jun aut Zhiyong, Peng aut Zhao, Xuemei aut Enthalten in Machine vision and applications Berlin : Springer, 1988 33(2022), 3 vom: 02. Apr. (DE-627)300186312 (DE-600)1481698-2 1432-1769 nnns volume:33 year:2022 number:3 day:02 month:04 https://dx.doi.org/10.1007/s00138-022-01296-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 3 02 04 |
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Huang, Mingyi @@aut@@ Wu, Jun @@aut@@ Zhiyong, Peng @@aut@@ Zhao, Xuemei @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR046655956</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230507175038.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220403s2022 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00138-022-01296-9</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR046655956</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00138-022-01296-9-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Huang, Mingyi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. 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Huang, Mingyi |
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High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) Fisheye lens calibration (dpeaa)DE-He213 Fisheye image correction (dpeaa)DE-He213 Spherical projection (dpeaa)DE-He213 Radial distortion projection ellipse constraint (dpeaa)DE-He213 |
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high-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (rdpec) |
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High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) |
| abstract |
Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
| abstract_unstemmed |
Abstract This paper presents a novel technique for wide-angle fisheye lens calibration which requires neither metric information nor particular reference pattern. First, the fisheye imaging model with the interior Orientation parameters (IOPs)—principal point (u0,v0), focal length f, aspect ratio λ and radial distortion coefficients (k1, k2), is established. Then, upon the fisheye imaging model and the parameter dependency between f and (k1, k2), the radial distortion projection ellipse constraint (RDPEC) for space lines in fisheye image is mathematically formulated to build a non-linear calibration model for high-precision estimation of the IOPs. In this step, parameter initialization based on the geometry of fisheye image outline ellipse (FIOE) is discussed as well. Finally, initial IOPs are further optimized though least square technique by taking the projection ellipse arcs of space lines in fisheye image as observation. The proposed calibration technique was tested on two kinds of fisheye images: (a) simulated image with a set of ground-truth IOPs, (b) internet images with unknown IOPs. Experimental results show that the calibration parameters in this paper are in the best agreement with the fisheye imaging model, compared with the ground-truth parameters and the parameters estimated by two state-of-the-art literature. Compared to that by a state-of-the-art CNN and the well-known software DXO, the proposed technique can enable a high-quality correction of fisheye images in different regions. This makes it very useful in application scenarios containing space lines, such as urban panorama surveillance, auto-parking and, robot navigation. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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High-precision calibration of wide-angle fisheye lens with radial distortion projection ellipse constraint (RDPEC) |
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Wu, Jun Zhiyong, Peng Zhao, Xuemei |
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10.1007/s00138-022-01296-9 |
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| score |
7.4007587 |