Abstract
Photogrammetric computer vision and laser scanning are two scientific fields whose analytical models are fundamentally based on geometrical transformations of point coordinates expressed in different reference frames. From the analytical point of view, the main problem of these transformations is that they are expressed, almost always, by nonlinear models. To solve the transformation problems, it is common to resort to the linearization of the original models and to the solution of inconsistent linearized systems of equations in order to reach, through the introduction of a proper error distribution model, the best estimation of the unknown parameters and of their precision. So, to carry out the computational procedure, it is necessary to determine, by a different method, the approximate value of the unknown parameters.
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© 2019 CISM International Centre for Mechanical Sciences
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Crosilla, F., Beinat, A., Fusiello, A., Maset, E., Visintini, D. (2019). Introduction. In: Advanced Procrustes Analysis Models in Photogrammetric Computer Vision. CISM International Centre for Mechanical Sciences, vol 590. Springer, Cham. https://doi.org/10.1007/978-3-030-11760-3_1
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DOI: https://doi.org/10.1007/978-3-030-11760-3_1
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