Visualization of the Past-to-Recent Changes in Cultural Heritage Based on 3D Digitization

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Abstract

3D digitization techniques, such as laser scanning and/or SfM (Structure from Motion), are often used for recording and documenting the archaeological heritages at many sites recently. As-is situations can be easily captured by those techniques for archiving the present geometrical information. Since excavation, different research teams might have conducted investigations and/or restoration work in different periods to date. Throughout the repeated re-excavation and backfill, there may be the places where some aspect dramatically changes. The photo records taken in the past investigations sometimes look very different from the present appearance and the differences are also difficult to describe and to record objectively. This paper proposes a methodology to support the collation of past photo data and current presence by image-processing. Estimating the 3D position and the orientation of the camera which took the photo in the past, by using correspondences between the pixels on the past photo and the reconstructed 3D shape of the current scene. By making corresponding pairs of the identical feature points between the past photo and the current 3D scene, solving PnP problem gives a good estimate of the camera viewpoint in the past. By rendering CG of the current 3D scene from the estimated viewpoint of the past camera, the CG and the past photo image can be aligned and overlaid precisely on the same view. This overlaid image allows to check the temporal changes of the object with pixel-unit precision and to help the maintenance work for inspection and repair. This paper applies to the actual site of Barbar temple at the Kingdom of Bahrain and shows the quantitative evaluation capability.

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APA

Mori, N., Higo, T., Suemori, K., Suita, H., & Yasumuro, Y. (2018). Visualization of the Past-to-Recent Changes in Cultural Heritage Based on 3D Digitization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11196 LNCS, pp. 3–14). Springer Verlag. https://doi.org/10.1007/978-3-030-01762-0_1

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