Abstract
This work reviews the anisotropic row-scaling variant of the Procrustes analysis algorithms applied to develop new analytical tools for solving classical photogrammetric Computer Vision problems. In Garro et al. (Solving the pnp problem with anisotropic orthogonal procrustes analysis, 2012) the anisotropic row-scaling Procrustes analysis was first applied to perform the exterior orientation of one image. Moreover Fusiello and Crosilla (ISPRS J Photogrammetry and Remote Sens 102:209–221, 2015) provided a Procrustean formulation of the photogrammetric bundle block adjustment problem. Procrustean methods do not require any linearization nor approximated values of the unknown parameters and the results obtained are comparable in terms of accuracy with those given by the state-of-the-art methods.
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Notes
- 1.
The vec operator transforms a matrix into a vector by stacking its columns.
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Crosilla, F., Maset, E., Fusiello, A. (2018). Procrustean Photogrammetry: From Exterior Orientation to Bundle Adjustment. In: Cefalo, R., Zieliński, J., Barbarella, M. (eds) New Advanced GNSS and 3D Spatial Techniques. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-56218-6_12
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DOI: https://doi.org/10.1007/978-3-319-56218-6_12
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