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Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
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Photogrammetric Computer Vision - Statistics, Geometry, Orientation and Reconstruction (Paperback, Softcover reprint of the original 1st ed. 2016)
Loot Price: R2,152
Discovery Miles 21 520
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Photogrammetric Computer Vision - Statistics, Geometry, Orientation and Reconstruction (Paperback, Softcover reprint of the original 1st ed. 2016)
Series: Geometry and Computing, 11
Expected to ship within 10 - 15 working days
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This textbook offers a statistical view on the geometry of multiple
view analysis, required for camera calibration and orientation and
for geometric scene reconstruction based on geometric image
features. The authors have backgrounds in geodesy and also long
experience with development and research in computer vision, and
this is the first book to present a joint approach from the
converging fields of photogrammetry and computer vision. Part I of
the book provides an introduction to estimation theory, covering
aspects such as Bayesian estimation, variance components, and
sequential estimation, with a focus on the statistically sound
diagnostics of estimation results essential in vision metrology.
Part II provides tools for 2D and 3D geometric reasoning using
projective geometry. This includes oriented projective geometry and
tools for statistically optimal estimation and test of geometric
entities and transformations and their rela tions, tools that are
useful also in the context of uncertain reasoning in point clouds.
Part III is de voted to modelling the geometry of single and
multiple cameras, addressing calibration and orienta tion,
including statistical evaluation and reconstruction of
corresponding scene features and surfaces based on geometric image
features. The authors provide algorithms for various geometric
computa tion problems in vision metrology, together with
mathematical justifications and statistical analysis, thus enabling
thorough evaluations. The chapters are self-contained with numerous
figures and exer cises, and they are supported by an appendix that
explains the basic mathematical notation and a de tailed index. The
book can serve as the basis for undergraduate and graduate courses
in photogrammetry, com puter vision, and computer graphics. It is
also appropriate for researchers, engineers, and software
developers in the photogrammetry and GIS industries, particularly
those engaged with statistically based geometric computer vision
methods.
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