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A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration.

Rau JY, Yeh PC - Sensors (Basel) (2012)

Bottom Line: This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object.The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner.The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333.

View Article: PubMed Central - PubMed

Affiliation: Department of Geomatics, National Cheng-Kung University, No.1, University Road, Tainan 701, Taiwan. jyrau@mail.ncku.edu.tw

ABSTRACT
The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum.

No MeSH data available.


Single camera calibration using a rotatable calibration field.
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f2-sensors-12-11271: Single camera calibration using a rotatable calibration field.

Mentions: The purpose of camera calibration is to mathematically describe the internal geometry of the imaging system, particularly after a light ray passes through the camera's perspective center. In order to determine such internal characteristics, a self-calibrating bundle adjustment method with additional parameters is adopted [28,29] that can automatically recognize and measure the image coordinates of retro-reflective coded targets. Based on this functionality, we develop a rotatable round table surmounted by 112 pillars. The coded targets are then fixed to the top of the pillars and the table surface to establish a three-dimensional calibration field with heights varying from 0 to 30 cm. Instead of changing the camera location during image acquisition, the table is simply rotated. Moreover, the camera's viewing direction is inclined 30°∼45° with respect to the table's surface normal. The concept for the acquisition of convergent geometry by means of a rotatable calibration field is illustrated in Figure 2. The round table is rotated at 45° intervals while capturing the calibration images. This results in 8 images with convergent angles of 60° to 90°, which is a strong convergent imaging geometry. In order to decouple the correlation between IOPs and EOPs during least-squares adjustment, it is suggested that an additional eight images be acquired with the camera rotated for portrait orientation, i.e., change roll angle with 90°. Finally, for the purpose of increasing image measurement redundancy, two additional images (landscape and portrait) are taken with the camera's optical axis perpendicular to the table surface.


A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration.

Rau JY, Yeh PC - Sensors (Basel) (2012)

Single camera calibration using a rotatable calibration field.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472884&req=5

f2-sensors-12-11271: Single camera calibration using a rotatable calibration field.
Mentions: The purpose of camera calibration is to mathematically describe the internal geometry of the imaging system, particularly after a light ray passes through the camera's perspective center. In order to determine such internal characteristics, a self-calibrating bundle adjustment method with additional parameters is adopted [28,29] that can automatically recognize and measure the image coordinates of retro-reflective coded targets. Based on this functionality, we develop a rotatable round table surmounted by 112 pillars. The coded targets are then fixed to the top of the pillars and the table surface to establish a three-dimensional calibration field with heights varying from 0 to 30 cm. Instead of changing the camera location during image acquisition, the table is simply rotated. Moreover, the camera's viewing direction is inclined 30°∼45° with respect to the table's surface normal. The concept for the acquisition of convergent geometry by means of a rotatable calibration field is illustrated in Figure 2. The round table is rotated at 45° intervals while capturing the calibration images. This results in 8 images with convergent angles of 60° to 90°, which is a strong convergent imaging geometry. In order to decouple the correlation between IOPs and EOPs during least-squares adjustment, it is suggested that an additional eight images be acquired with the camera rotated for portrait orientation, i.e., change roll angle with 90°. Finally, for the purpose of increasing image measurement redundancy, two additional images (landscape and portrait) are taken with the camera's optical axis perpendicular to the table surface.

Bottom Line: This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object.The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner.The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333.

View Article: PubMed Central - PubMed

Affiliation: Department of Geomatics, National Cheng-Kung University, No.1, University Road, Tainan 701, Taiwan. jyrau@mail.ncku.edu.tw

ABSTRACT
The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum.

No MeSH data available.