Overview
- Unique reference for Procrustean methods applied to Photogrammetry and Computer Vision
- Innovative and unconventional mathematical approach to fundamentals of Photogrammetry and Computer Vision
- Complements the book “Photogrammetric Computer Vision” by Förstner and Wrobel (Springer 2016)
Part of the book series: CISM International Centre for Mechanical Sciences (CISM, volume 590)
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Table of contents (9 chapters)
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Front Matter
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Theory of Procrustes Analysis Models
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Front Matter
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An Introduction to Computer Vision and Laser Scanning
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Front Matter
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Applications of Procrustes Analysis Models
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Front Matter
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Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Advanced Procrustes Analysis Models in Photogrammetric Computer Vision
Authors: Fabio Crosilla, Alberto Beinat, Andrea Fusiello, Eleonora Maset, Domenico Visintini
Series Title: CISM International Centre for Mechanical Sciences
DOI: https://doi.org/10.1007/978-3-030-11760-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: CISM International Centre for Mechanical Sciences 2019
Hardcover ISBN: 978-3-030-11759-7Published: 08 March 2019
eBook ISBN: 978-3-030-11760-3Published: 28 February 2019
Series ISSN: 0254-1971
Series E-ISSN: 2309-3706
Edition Number: 1
Number of Pages: XI, 172
Number of Illustrations: 7 b/w illustrations, 59 illustrations in colour
Topics: Remote Sensing/Photogrammetry, Image Processing and Computer Vision