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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.


A sample image for camera calibration and two enlarged code targets.
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f3-sensors-12-11271: A sample image for camera calibration and two enlarged code targets.

Mentions: The relative position of all the code targets is firmly fixed and remains stationary during rotation. This is essentially the same as surrounding the calibration field and taking pictures, introducing a ring type convergent imaging geometry. The proposed ring type configuration is difficult to obtain with a fixed calibration field and particularly for a limited space where the floor and ceiling will constrain the camera's location. A sample image for camera calibration is illustrated in Figure 3. One may observe that the coded targets are well spread out to the whole image frame, especially the image corners, where the most critical regions to describe the radial lens distortion are. In the figure, the bigger white dots are designed for low resolution cameras to increase the number of tie-point measurements by the auto-referencing function. The auto-referencing is performed by predicting the detected white dots from one image to the others using epipolar geometry in case the relative orientation has been established in advance by means of code targets. Meanwhile, Figure 3 also shows two enlarged code targets. In each coded target, two distance observables are constructed by four white points and utilized for scaling purposes during bundle adjustment. This means that the absolute positioning accuracy can be estimated for the calibrated IOPs. Figure 4 depicts the result of bundle convergence for one target from all cameras. The results demonstrate that it is possible to obtain a strong imaging geometry by means of the proposed arrangement.


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

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

A sample image for camera calibration and two enlarged code targets.
© Copyright Policy
Related In: Results  -  Collection

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

f3-sensors-12-11271: A sample image for camera calibration and two enlarged code targets.
Mentions: The relative position of all the code targets is firmly fixed and remains stationary during rotation. This is essentially the same as surrounding the calibration field and taking pictures, introducing a ring type convergent imaging geometry. The proposed ring type configuration is difficult to obtain with a fixed calibration field and particularly for a limited space where the floor and ceiling will constrain the camera's location. A sample image for camera calibration is illustrated in Figure 3. One may observe that the coded targets are well spread out to the whole image frame, especially the image corners, where the most critical regions to describe the radial lens distortion are. In the figure, the bigger white dots are designed for low resolution cameras to increase the number of tie-point measurements by the auto-referencing function. The auto-referencing is performed by predicting the detected white dots from one image to the others using epipolar geometry in case the relative orientation has been established in advance by means of code targets. Meanwhile, Figure 3 also shows two enlarged code targets. In each coded target, two distance observables are constructed by four white points and utilized for scaling purposes during bundle adjustment. This means that the absolute positioning accuracy can be estimated for the calibrated IOPs. Figure 4 depicts the result of bundle convergence for one target from all cameras. The results demonstrate that it is possible to obtain a strong imaging geometry by means of the proposed arrangement.

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.