Guide to 3D Vision Computation: Geometric Analysis and Implementation
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.
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Guide to 3D Vision Computation: Geometric Analysis and Implementation
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.
54.99 In Stock
Guide to 3D Vision Computation: Geometric Analysis and Implementation

Guide to 3D Vision Computation: Geometric Analysis and Implementation

Guide to 3D Vision Computation: Geometric Analysis and Implementation

Guide to 3D Vision Computation: Geometric Analysis and Implementation

eBook1st ed. 2016 (1st ed. 2016)

$54.99 

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Overview

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.

Product Details

ISBN-13: 9783319484938
Publisher: Springer International Publishing
Publication date: 12/09/2016
Series: Advances in Computer Vision and Pattern Recognition
Sold by: Barnes & Noble
Format: eBook
File size: 12 MB
Note: This product may take a few minutes to download.

About the Author

Dr. Kenichi Kanatani is a Professor Emeritus at Okayama University, Japan. Drs. Yasuyuki Sugaya and Yasushi Kanazawa are Associate Professors in the Department of Computer Science and Engineering at Toyohashi University of Technology, Japan.

Table of Contents

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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