Guide to 3D vision computation : geometric analysis and implementation
著者
書誌事項
Guide to 3D vision computation : geometric analysis and implementation
（Advances in computer vision and pattern recognition / Sameer Singh, Sing Bing Kang, series editors）
Springer International Publishing AG, c2016
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注記
Index: p. 319-321
内容説明・目次
内容説明
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 computer vision textbooks, this guide 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. Features: reviews the fundamental algorithms underlying computer vision; describes the latest techniques for 3D reconstruction from multiple images; summarizes the mathematical theory behind statistical error analysis for general geometric estimation problems; presents derivations at the end of each chapter, with solutions supplied at the end of the book; provides additional material at an associated website.
目次
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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