Determination of St. George Basilica Tower Historical Inclination from Contemporary Photograph

Bronislav Koska

Abstract


A large amount of photographic material has been accumulated from the photography emerge in the nineteenth century. The most photographs record portraits, urbanistic complex, significant architecture and others important objects in the photography inception. Historical photographs recorded a huge amount of information, which can be use for various research activities. Photograph visual information is sufficient in many cases, but accurate geometrical information must be acquired from it in specific situations. It is the case of long-term stability monitoring of buildings in the Prague Castle area see [1]. For static analysis in the monitoring project, it is necessary to determine accurately specific geometrical parameter – mutual angle of St. George Basilica towers in the north-south direction before the reconstruction started in 1888. The angle standard deviation must be solved as well. The task demanded using of photogrammetric methods. Own implementation of general bundle adjustment had to be created to fulfill determination of reliable standard deviation of the angle, because standard photogrammetric software does not have all the necessary options.

Keywords


photogrammetry, bundle adjustment, datum problem, free network adjustment, covariant matrix

References


Procházka, J., Záleský, J., Jiřikovský, T., Salák, J.: Long-term Stability Monitoring in the Prague Castle Area, Acta Geodynamica et Geomaterialia. Vol. 7, no. 4, p. 411-429, 2010.

McGlone, J. Ch. (Editor), Mikhail, E. M. (Editor), Bethel, J. S. (Editor), Mullen, R. (Contributor): Manual of Photogrammetry – Fifth Edition, ASPRS, 2004, ISBN 1570830711.

Triggs, B., McLauchlan, P., Hartley, R., Fitzgibbon, A.: Bundle Adjustment - A Modern Synthesis, Vision algorithms theory and practice, Springer, vol. 34099, p.: 298-372, 2000, ISBN: 3540679731. Available online:

Koch, K-R.: Parameter Estimation and Hypothesis Testing in Linear Models, Springer, Germany, 1999.


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