Advanced procrustes analysis models in photogrammetric computer vision /

This book gives a comprehensive view of the developed procrustes models, including the isotropic, the generalized and the anisotropic variants. These represent original tools to perform, among others, the bundle block adjustment and the global registration of multiple 3D LiDAR point clouds. Moreover...

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Bibliographic Details
Main Author: Crosilla, Fabio (Autor/a)
Other Authors: Beinat, Alberto (Autor/a), Fusiello, Andrea 1968- (Autor/a), Maset, Eleonora (Autor/a), Visintini, Domenico (Autor/a)
Format: Book
Language:English
Published: Cham, Switzerland : Springer, [2019].
Series:CISM International Centre for Mechanical Sciences. Courses and Lectures / series editors Elisabeth Guazzelli, Franz G. Rammerstorfer, Wolfgang A. Wall, Bernhard Schrefler volume 590
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Online Access:Ver documento en línea
Description
Summary:This book gives a comprehensive view of the developed procrustes models, including the isotropic, the generalized and the anisotropic variants. These represent original tools to perform, among others, the bundle block adjustment and the global registration of multiple 3D LiDAR point clouds. Moreover, the book also reports the recently derived total least squares solution of the anisotropic Procrustes model, together with its practical application in solving the exterior orientation of one image. The book is aimed at all those interested in discovering valuable innovative algorithms for solving various photogrammetric computer vision problems. In this context, where functional models are non-linear, Procrustean methods prove to be powerful since they do not require any linearization nor approximated values of the unknown parameters, furnishing at the same time results comparable in terms of accuracy with those given by the state-of-the-art methods.
Physical Description:1 recurso en línea (xi, 172 páginas) : ilustraciones (principalmente a color), gráficos a color, fotografías a color, archivo de texto, PDF.
ISBN:9783030117603
9783030117597
Access:Acceso al texto completo para la comunidad de la UCR por medio de la cuenta institucional