Guide to 3D vision computation : geometric analysis and implementation / Kenichi Kanatani, Yasuyuki Sugaya, Yasushi Kanazawa.
Kanatani, Kenichi; Sugaya, Yasuyuki, author; Kanazawa, Yasushi, author
2016
TA1634
Available Online

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Title Guide to 3D vision computation : geometric analysis and implementation / Kenichi Kanatani, Yasuyuki Sugaya, Yasushi Kanazawa.
Author Kanatani, Kenichi
ISBN 9783319484938 (electronic book)
3319484931 (electronic book)
9783319484921
DOI https://doi.org/10.1007/978-3-319-48493-8
Published Cham : Springer, 2016
Language English
Description 1 online resource (xi, 321 pages) : illustrations.
Item Number 10.1007/978-3-319-48493-8 doi
Call Number TA1634
Dewey Decimal Classification 006.6
006.37
Summary This classroom-tested and easy-to-understand textbook/reference describes the state of the art in 3D reconstruction from multiple images, taking into consideration all aspects of programming and implementation. Unlike other textbooks on computer vision, this Guide to 3D Vision Computation takes a unique approach in which the initial focus is on practical application and the procedures necessary to actually build a computer vision system. The theoretical background is then briefly explained afterwards, highlighting how one can quickly and simply obtain the desired result without knowing the derivation of the mathematical detail. Topics and features: Reviews the fundamental algorithms underlying computer vision, and their implementation Describes the latest techniques for 3D reconstruction from multiple images Summarizes the mathematical theory behind statistical error analysis for general geometric estimation problems Offers examples of experimental results, enabling the reader to get a feeling of what can be done using each procedure Presents derivations and justifications as problems at the end of each chapter, with solutions supplied at the end of the book Explains the historical background for each topic in the supplemental notes at the end of each chapter Provides additional material at an associated website, include sample code for typical procedures to help readers implement the algorithms described in the book This accessible work will be of great value to students on introductory computer vision courses. Serving as both as a practical programming guidebook and a useful reference on mathematics for computer vision, it is suitable for practitioners seeking to implement computer vision algorithms as well as for theoreticians wishing to know the underlying mathematical detail
Note This classroom-tested and easy-to-understand textbook/reference describes the state of the art in 3D reconstruction from multiple images, taking into consideration all aspects of programming and implementation. Unlike other textbooks on computer vision, this Guide to 3D Vision Computation takes a unique approach in which the initial focus is on practical application and the procedures necessary to actually build a computer vision system. The theoretical background is then briefly explained afterwards, highlighting how one can quickly and simply obtain the desired result without knowing the derivation of the mathematical detail. Topics and features: Reviews the fundamental algorithms underlying computer vision, and their implementation Describes the latest techniques for 3D reconstruction from multiple images Summarizes the mathematical theory behind statistical error analysis for general geometric estimation problems Offers examples of experimental results, enabling the reader to get a feeling of what can be done using each procedure Presents derivations and justifications as problems at the end of each chapter, with solutions supplied at the end of the book Explains the historical background for each topic in the supplemental notes at the end of each chapter Provides additional material at an associated website, include sample code for typical procedures to help readers implement the algorithms described in the book This accessible work will be of great value to students on introductory computer vision courses. Serving as both as a practical programming guidebook and a useful reference on mathematics for computer vision, it is suitable for practitioners seeking to implement computer vision algorithms as well as for theoreticians wishing to know the underlying mathematical detail
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Added Author Sugaya, Yasuyuki, author
Kanazawa, Yasushi, author
Series Advances in computer vision and pattern recognition, 2191-6586
Available in Other Form Print version: 9783319484921
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Record Appears in Online Resources > Ebooks
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Introduction
Part I: Fundamental Algorithms for Computer Vision
Ellipse Fitting
Fundamental Matrix Computation
Triangulation
3D Reconstruction from Two Views
Homography Computation
Planar Triangulation
3D Reconstruction of a Plane
Ellipse Analysis and 3D Computation of Circles
Part II: Multiview 3D Reconstruction
Multiview Triangulation
Bundle Adjustment
Self-calibration of Affine Cameras
Self-calibration of Perspective Cameras
Part III: Mathematical Foundation of Geometric Estimation
Accuracy of Geometric Estimation
Maximum Likelihood and Geometric Estimation
Theoretical Accuracy Limit
Solutions

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