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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.


The flow-chart of the proposed 3D modeling pipeline.
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f1-sensors-12-11271: The flow-chart of the proposed 3D modeling pipeline.

Mentions: There are two stages in the proposed 3D modeling pipeline, as shown in Figure 1. In the calibration stage, the IOPs of each camera are calibrated independently using coded targets through a self-calibration bundle adjustment with additional parameters [28]. This process can be performed fully automatically and should be done when the camera's status has changed. Then, the cameras are installed on a curved metal bar(s) designed to maintain their relative orientation, which is important when dealing with large quantity of objects that require long period of working day. A strong convergent imaging geometry is constructed for better positioning accuracy. The EOPs of all the cameras are again calibrated automatically by means of the coded targets [28]. This procedure needs to be applied every time any camera is reinstalled.


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

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

The flow-chart of the proposed 3D modeling pipeline.
© Copyright Policy
Related In: Results  -  Collection

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

f1-sensors-12-11271: The flow-chart of the proposed 3D modeling pipeline.
Mentions: There are two stages in the proposed 3D modeling pipeline, as shown in Figure 1. In the calibration stage, the IOPs of each camera are calibrated independently using coded targets through a self-calibration bundle adjustment with additional parameters [28]. This process can be performed fully automatically and should be done when the camera's status has changed. Then, the cameras are installed on a curved metal bar(s) designed to maintain their relative orientation, which is important when dealing with large quantity of objects that require long period of working day. A strong convergent imaging geometry is constructed for better positioning accuracy. The EOPs of all the cameras are again calibrated automatically by means of the coded targets [28]. This procedure needs to be applied every time any camera is reinstalled.

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.