Photogrammetric Computer Vision Statistics, Geometry, Orientation and Reconstruction

This includes oriented projective geometry and tools for statistically optimal estimation and test of geometric entities and transformations and their rela­tions, tools that are useful also in the context of uncertain reasoning in point clouds. Part III is de­voted to modelling the geometry of singl...

Full description

Bibliographic Details
Main Authors: Förstner, Wolfgang, Wrobel, Bernhard P. (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2016, 2016
Edition:1st ed. 2016
Series:Geometry and Computing
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
LEADER 03779nmm a2200361 u 4500
001 EB001266139
003 EBX01000000000000000880723
005 00000000000000.0
007 cr|||||||||||||||||||||
008 161103 ||| eng
020 |a 9783319115504 
100 1 |a Förstner, Wolfgang 
245 0 0 |a Photogrammetric Computer Vision  |h Elektronische Ressource  |b Statistics, Geometry, Orientation and Reconstruction  |c by Wolfgang Förstner, Bernhard P. Wrobel 
250 |a 1st ed. 2016 
260 |a Cham  |b Springer International Publishing  |c 2016, 2016 
300 |a XVII, 816 p. 281 illus., 59 illus. in color  |b online resource 
505 0 |a Introduction -- Tasks for Photogrammetric Computer Vision -- Modelling in Automated Photogrammetric Computer Vision -- Probability Theory and Random Variables -- Testing -- Estimation -- Homogeneous Representations of Points, Lines and Planes -- Transformations -- Geometric Operations -- Rotations -- Oriented Projective Geometry -- Reasoning with Uncertain Geometric Entities -- Orientation and Reconstruction -- Bundle Adjustment -- Surface Reconstruction from Point Clouds -- References -- Index 
653 |a Image processing / Digital techniques 
653 |a Geographical Information System 
653 |a Computer vision 
653 |a Computer Imaging, Vision, Pattern Recognition and Graphics 
653 |a Geometry 
653 |a Geographic information systems 
700 1 |a Wrobel, Bernhard P.  |e [author] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b Springer  |a Springer eBooks 2005- 
490 0 |a Geometry and Computing 
028 5 0 |a 10.1007/978-3-319-11550-4 
856 4 0 |u https://doi.org/10.1007/978-3-319-11550-4?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 006 
520 |a This includes oriented projective geometry and tools for statistically optimal estimation and test of geometric entities and transformations and their rela­tions, tools that are useful also in the context of uncertain reasoning in point clouds. Part III is de­voted to modelling the geometry of single and multiple cameras, addressing calibration and orienta­tion, including statistical evaluation and reconstruction of corresponding scene features and surfaces based on geometric image features. The authors provide algorithms for various geometric computa­tion problems in vision metrology, together with mathematical justifications and statistical analysis, thus enabling thorough evaluations. The chapters are self-contained with numerous figures and exer­cises, and they are supported by an appendix that explains the basic mathematical notation and a de­tailed index.  
520 |a 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.  
520 |a The book can serve as the basis for undergraduate and graduate courses in photogrammetry, com­puter 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