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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.


Human model generated by the proposed scheme.
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f16-sensors-12-11271: Human model generated by the proposed scheme.

Mentions: In this case study, the proposed close range 3D modeling pipeline is utilized to generate 3D models of a human body and eight Buddhist statues to test its feasibility. The results are illustrated in Figures 16 and 17. For convenient, all of them utilize the 1 × 5 multi-camera configuration because only one metal bar is required. One may observe that the generated 3D models have a higher level of detail in the structure. It is particularly obvious for the Buddhist statues as compared with the human model. This is majorly because the human image has less texture on its surface. The 3D model results of Buddhist statues demonstrate that the proposed scheme would be useful for digital recording of cultural heritage objects. Major museums normally pose hundreds or even thousands of statues, vases, antiques, etc., of similar size. In such cases, it would be very efficient to utilize the proposed scheme by changing the objects while retaining the multi-camera configuration all the time.


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

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

Human model generated by the proposed scheme.
© Copyright Policy
Related In: Results  -  Collection

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

f16-sensors-12-11271: Human model generated by the proposed scheme.
Mentions: In this case study, the proposed close range 3D modeling pipeline is utilized to generate 3D models of a human body and eight Buddhist statues to test its feasibility. The results are illustrated in Figures 16 and 17. For convenient, all of them utilize the 1 × 5 multi-camera configuration because only one metal bar is required. One may observe that the generated 3D models have a higher level of detail in the structure. It is particularly obvious for the Buddhist statues as compared with the human model. This is majorly because the human image has less texture on its surface. The 3D model results of Buddhist statues demonstrate that the proposed scheme would be useful for digital recording of cultural heritage objects. Major museums normally pose hundreds or even thousands of statues, vases, antiques, etc., of similar size. In such cases, it would be very efficient to utilize the proposed scheme by changing the objects while retaining the multi-camera configuration all the time.

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.