Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes
Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for t...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Stamos, Ioannis [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2007 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC 2007 |
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| Übergeordnetes Werk: |
Enthalten in: International journal of computer vision - Springer US, 1987, 78(2007), 2-3 vom: 10. Nov., Seite 237-260 |
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| Übergeordnetes Werk: |
volume:78 ; year:2007 ; number:2-3 ; day:10 ; month:11 ; pages:237-260 |
| Links: |
|---|
| DOI / URN: |
10.1007/s11263-007-0089-1 |
|---|
| Katalog-ID: |
OLC2057742989 |
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| 520 | |a Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. | ||
| 650 | 4 | |a Range segmentation | |
| 650 | 4 | |a Range-to-range registration | |
| 650 | 4 | |a Range-to-image registration | |
| 650 | 4 | |a Multiview geometry | |
| 650 | 4 | |a Structure from motion | |
| 650 | 4 | |a Photorealistic modeling | |
| 700 | 1 | |a Liu, Lingyun |4 aut | |
| 700 | 1 | |a Chen, Chao |4 aut | |
| 700 | 1 | |a Wolberg, George |4 aut | |
| 700 | 1 | |a Yu, Gene |4 aut | |
| 700 | 1 | |a Zokai, Siavash |4 aut | |
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10.1007/s11263-007-0089-1 doi (DE-627)OLC2057742989 (DE-He213)s11263-007-0089-1-p DE-627 ger DE-627 rakwb eng 004 VZ Stamos, Ioannis verfasserin aut Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2007 Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. Range segmentation Range-to-range registration Range-to-image registration Multiview geometry Structure from motion Photorealistic modeling Liu, Lingyun aut Chen, Chao aut Wolberg, George aut Yu, Gene aut Zokai, Siavash aut Enthalten in International journal of computer vision Springer US, 1987 78(2007), 2-3 vom: 10. Nov., Seite 237-260 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:78 year:2007 number:2-3 day:10 month:11 pages:237-260 https://doi.org/10.1007/s11263-007-0089-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_70 GBV_ILN_100 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2244 GBV_ILN_4046 GBV_ILN_4700 AR 78 2007 2-3 10 11 237-260 |
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10.1007/s11263-007-0089-1 doi (DE-627)OLC2057742989 (DE-He213)s11263-007-0089-1-p DE-627 ger DE-627 rakwb eng 004 VZ Stamos, Ioannis verfasserin aut Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2007 Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. Range segmentation Range-to-range registration Range-to-image registration Multiview geometry Structure from motion Photorealistic modeling Liu, Lingyun aut Chen, Chao aut Wolberg, George aut Yu, Gene aut Zokai, Siavash aut Enthalten in International journal of computer vision Springer US, 1987 78(2007), 2-3 vom: 10. Nov., Seite 237-260 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:78 year:2007 number:2-3 day:10 month:11 pages:237-260 https://doi.org/10.1007/s11263-007-0089-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_70 GBV_ILN_100 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2244 GBV_ILN_4046 GBV_ILN_4700 AR 78 2007 2-3 10 11 237-260 |
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10.1007/s11263-007-0089-1 doi (DE-627)OLC2057742989 (DE-He213)s11263-007-0089-1-p DE-627 ger DE-627 rakwb eng 004 VZ Stamos, Ioannis verfasserin aut Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2007 Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. Range segmentation Range-to-range registration Range-to-image registration Multiview geometry Structure from motion Photorealistic modeling Liu, Lingyun aut Chen, Chao aut Wolberg, George aut Yu, Gene aut Zokai, Siavash aut Enthalten in International journal of computer vision Springer US, 1987 78(2007), 2-3 vom: 10. Nov., Seite 237-260 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:78 year:2007 number:2-3 day:10 month:11 pages:237-260 https://doi.org/10.1007/s11263-007-0089-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_70 GBV_ILN_100 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2244 GBV_ILN_4046 GBV_ILN_4700 AR 78 2007 2-3 10 11 237-260 |
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10.1007/s11263-007-0089-1 doi (DE-627)OLC2057742989 (DE-He213)s11263-007-0089-1-p DE-627 ger DE-627 rakwb eng 004 VZ Stamos, Ioannis verfasserin aut Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2007 Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. Range segmentation Range-to-range registration Range-to-image registration Multiview geometry Structure from motion Photorealistic modeling Liu, Lingyun aut Chen, Chao aut Wolberg, George aut Yu, Gene aut Zokai, Siavash aut Enthalten in International journal of computer vision Springer US, 1987 78(2007), 2-3 vom: 10. Nov., Seite 237-260 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:78 year:2007 number:2-3 day:10 month:11 pages:237-260 https://doi.org/10.1007/s11263-007-0089-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_70 GBV_ILN_100 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2244 GBV_ILN_4046 GBV_ILN_4700 AR 78 2007 2-3 10 11 237-260 |
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10.1007/s11263-007-0089-1 doi (DE-627)OLC2057742989 (DE-He213)s11263-007-0089-1-p DE-627 ger DE-627 rakwb eng 004 VZ Stamos, Ioannis verfasserin aut Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC 2007 Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. Range segmentation Range-to-range registration Range-to-image registration Multiview geometry Structure from motion Photorealistic modeling Liu, Lingyun aut Chen, Chao aut Wolberg, George aut Yu, Gene aut Zokai, Siavash aut Enthalten in International journal of computer vision Springer US, 1987 78(2007), 2-3 vom: 10. Nov., Seite 237-260 (DE-627)129354252 (DE-600)155895-X (DE-576)018081428 0920-5691 nnns volume:78 year:2007 number:2-3 day:10 month:11 pages:237-260 https://doi.org/10.1007/s11263-007-0089-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_70 GBV_ILN_100 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2012 GBV_ILN_2244 GBV_ILN_4046 GBV_ILN_4700 AR 78 2007 2-3 10 11 237-260 |
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integrating automated range registration with multiview geometry for the photorealistic modeling of large-scale scenes |
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Integrating Automated Range Registration with Multiview Geometry for the Photorealistic Modeling of Large-Scale Scenes |
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Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. © Springer Science+Business Media, LLC 2007 |
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Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. © Springer Science+Business Media, LLC 2007 |
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Abstract The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes. © Springer Science+Business Media, LLC 2007 |
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