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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.


Adopted multi-camera frameworks. (A) The 1 × 5 Multi-Camera Configuration. (B) The 2 + 3 Multi-Camera Configuration.
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f5-sensors-12-11271: Adopted multi-camera frameworks. (A) The 1 × 5 Multi-Camera Configuration. (B) The 2 + 3 Multi-Camera Configuration.

Mentions: The original development of the adopted multiple image matching software is based on conventional stripped aerial images. Thus, in this study two types of multi-camera configurations were proposed, namely the 1 × 5 and 2 + 3 configurations. Figure 5 illustrates the setup of cameras in the proposed multi-camera configurations. In which, the cameras' numbers are denoted and used in the case studies. Several combinations based on those two configurations are compared. In the first setup, five SONY A850 DSLR digital cameras are fixed to a curved metal bar (1.5 meters long), as shown in Figure 5(A), while in the second configuration we use two curved metal bars, as illustrated in Figure 5(B). In the latter case, the lower metal bar has three cameras and the higher one has two. The two metal bars are setup parallel to each other with approximately 30 cm apart. This design is used in multi-image matching to avoid ambiguity problems when searching for candidates along the epipolar line [34]. For better positioning accuracy, the convergent imaging scheme is adopted [19]. For the purpose of synchronous imaging, which is important when the target is a live object, the cameras' triggers are connected in parallel and can be controlled either manually or automatically by a computer. With the 1 × 5 configuration, for an object located at 1.5 meters from the camera, the base-to-depth (B/D) ratios for all camera combinations range from approximately 0.2 to 0.8. The largest B/D ratio will provide accurate space intersection results, whereas the shortest one will introduce less geometric differences which is suitable for area-based image matching. In the experiments, several base-to-depth combinations are tested to evaluate the performance of different multi-camera configurations.


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

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

Adopted multi-camera frameworks. (A) The 1 × 5 Multi-Camera Configuration. (B) The 2 + 3 Multi-Camera Configuration.
© Copyright Policy
Related In: Results  -  Collection

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

f5-sensors-12-11271: Adopted multi-camera frameworks. (A) The 1 × 5 Multi-Camera Configuration. (B) The 2 + 3 Multi-Camera Configuration.
Mentions: The original development of the adopted multiple image matching software is based on conventional stripped aerial images. Thus, in this study two types of multi-camera configurations were proposed, namely the 1 × 5 and 2 + 3 configurations. Figure 5 illustrates the setup of cameras in the proposed multi-camera configurations. In which, the cameras' numbers are denoted and used in the case studies. Several combinations based on those two configurations are compared. In the first setup, five SONY A850 DSLR digital cameras are fixed to a curved metal bar (1.5 meters long), as shown in Figure 5(A), while in the second configuration we use two curved metal bars, as illustrated in Figure 5(B). In the latter case, the lower metal bar has three cameras and the higher one has two. The two metal bars are setup parallel to each other with approximately 30 cm apart. This design is used in multi-image matching to avoid ambiguity problems when searching for candidates along the epipolar line [34]. For better positioning accuracy, the convergent imaging scheme is adopted [19]. For the purpose of synchronous imaging, which is important when the target is a live object, the cameras' triggers are connected in parallel and can be controlled either manually or automatically by a computer. With the 1 × 5 configuration, for an object located at 1.5 meters from the camera, the base-to-depth (B/D) ratios for all camera combinations range from approximately 0.2 to 0.8. The largest B/D ratio will provide accurate space intersection results, whereas the shortest one will introduce less geometric differences which is suitable for area-based image matching. In the experiments, several base-to-depth combinations are tested to evaluate the performance of different multi-camera configurations.

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.