PROBABILISTIC FEASIBILITY OF THE RECONSTRUCTION PROCESS OF RUSSIAN-ORTHODOX CHURCHES
The cultural human heritage is important for the identity of following generations and has to be preserved in a suitable manner. In the course of time a lot of information about former cultural constructions has been lost because some objects were strongly damaged by natural erosion or on account...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2016-06-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B5/221/2016/isprs-archives-XLI-B5-221-2016.pdf |
Summary: | The cultural human heritage is important for the identity of following generations and has to be preserved in a suitable manner. In the
course of time a lot of information about former cultural constructions has been lost because some objects were strongly damaged by
natural erosion or on account of human work or were even destroyed. It is important to capture still available building parts of former
buildings, mostly ruins. This data could be the basis for a virtual reconstruction. Laserscanning offers in principle the possibility to
take up extensively surfaces of buildings in its actual status.
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In this paper we assume a priori given 3d-laserscanner data, 3d point cloud for the partly destroyed church. There are many well known
algorithms, that describe different methods of extraction and detection of geometric primitives, which are recognized separately in 3d
points clouds. In our work we put them in a common probabilistic framework, which guides the complete reconstruction process of
complex buildings, in our case russian-orthodox churches.
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Churches are modeled with their functional volumetric components, enriched with a priori known probabilities, which are deduced
from a database of russian-orthodox churches. Each set of components represents a complete church. The power of the new method is
shown for a simulated dataset of 100 russian-orthodox churches. |
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ISSN: | 1682-1750 2194-9034 |