Advanced Procrustes Analysis Models in Photogrammetric Computer Vision - Fabio Crosilla, Alberto Beinat, Andrea Fusiello, Eleonora Maset, Domenico Visintini

Advanced Procrustes Analysis Models in Photogrammetric Computer Vision

Buch | Hardcover
XI, 172 Seiten
2019 | 1st ed. 2019
Springer International Publishing (Verlag)
978-3-030-11759-7 (ISBN)
106,99 inkl. MwSt

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.

Theory of procrustes analysis models.- An introduction to computer vision and laser scanning.- Applications of procrustes analysis models

Erscheinungsdatum
Reihe/Serie CISM International Centre for Mechanical Sciences
Zusatzinfo XI, 172 p. 66 illus., 59 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 444 g
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Naturwissenschaften Geowissenschaften Geografie / Kartografie
Schlagworte Algebraic Techniques • Bundle adjustment • Point clouds registration • Procrustes analysis • Procrustes problems • Remote Sensing/Photogrammetry
ISBN-10 3-030-11759-6 / 3030117596
ISBN-13 978-3-030-11759-7 / 9783030117597
Zustand Neuware
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