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Vision based technique for photorealistic 3D reconstruction of historical items
Texture Generation
Because of complicated topology of most of historical artifacts (e.g. sculpture or skull) a set of images in shadow-free light is needed for generating photorealistic texture. The number of images is depends on object topology and is chosen parameter.
To generate metric texture for reconstructed 3D model several images are acquired from all three cameras at given positions of turntable. Then 3D model is divided into corresponding fragments basing on turntable position. For each fragment texture is generated as orthophoto.
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Figure 4. The image and textured 3D model of American Indian vase
Fig. 4. shows the object (American Indian vase) image (a) and the result of textured 3D model reconstruction (b). Seven images were used for texture: three images from left camera, two images from right camera and two images from upper camera (for bottom texturing).
Fig. 4. demonstrates good quality of texture mapping but also shows a need for shadow-free light improvement to eliminate brightness difference near fragments' borders.
Discussions and Conclusions
Automated PC-based digital photogrammetric system for 3D reconstruction such complex spatial objects as historical artifacts is developed. It provides obtaining the whole object 3D model by one step using three CCD cameras and PC-controlled turntable. Automated correspondence problem solution is provided by image acquisition in stripe structural light.
High precision of 3D reconstruction and texture mapping for non-metric CCD cameras used for image acquisition are provided by preliminary calibration. Calibration includes cameras interior and exterior orientation and estimation of orientation turntable rotation axis and structured light plane. Calibration process has high degree of automation due to coded target applying.
After calibration stage process of 3D reconstruction and texture mapping is fully automated and can be performed by "one-button-click". The time required for one 3D model generation in start-stop mode is about 4 minutes, the most time consuming part of process (about 75%) being table rotation. The accuracy of spatial coordinate determination is at the level of 0.15mm, the point density is 100 000 points per 3D model.
Photorealistic texture is generated basing on a set of images acquired in shadow-free lighting. The accuracy in texture continuity at the places of different images bordering is about 1/3 pixel. High quality of texture mapping provides additional wide capacities for expert work.
The results of system application for real object 3D reconstruction demonstrate that the developed system provides high accuracy of produced 3D models and reasonable performance. The quality of produced 3D models are adequate for wide variety of virtual reality applications. The higher productivity can be achieved in real-time mode, which requires applying of advanced frame grabber.
References
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Chikatsu H., 1997, Anaj T., Hatano K. Real-time Ortho Imaging and Surface Modeling for Archeological Artifacts. Optical 3D Measurement Techniques IV, Edited by A.Gruen, O.Kuhbler, Zurich, 29 September- 2 October, 1997, pp. 19-26
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Knyaz V.A., 1998, A. V. Sibiryakov. The Development of New Coded Targets for Automated point Identification and Non-contact 3D Surface Measurements, International Archives of Photogrammetry and Remote Sensing, Vol. XXXII, part 5, Hakodate, Japan, 1998, pp. 80-85.
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Knyaz V.A., 1999, S.Yu. Zheltov, D.G. Stepanyants. Method for accurate camera orientation for automobile photogrammetric system. Proceedings of International Workshop on Mobile Mapping Technology, Bangkok, Thailand, April 21-23,1999, pp.4-3-1 - 4-3-6
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Beyer H.A., 1992. Accurate Calibration of CCD-Cameras, Proceedings of the IEEE Computer Society Conferencion Computer Vision & Pattern Recognition 1992 (CVPR92), Champaign, Illinois, June 1992, pp. 96-101
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Knyaz V. A., 2000, S. Yu. Zheltov. Approach to Accurate Photorealistic Model Generation for Complex 3D Objects. International Archives of Photogrammetry and Remote Sensing, Vol. XXXIII, part B5/1, Amsterdam, The Netherlands, 2000, pp. 428-433
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