000 -LEADER |
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06897nam a22004335i 4500 |
003 - CONTROL NUMBER IDENTIFIER |
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005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20140310143359.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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120101s2012 ne | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9789400726543 |
|
978-94-007-2654-3 |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
629.892 |
Edition number |
23 |
264 #1 - |
-- |
Dordrecht : |
-- |
Springer Netherlands : |
-- |
Imprint: Springer, |
-- |
2012. |
912 ## - |
-- |
ZDB-2-ENG |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Zhang, Beiwei. |
Relator term |
author. |
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
Title |
Automatic Calibration and Reconstruction for Active Vision Systems |
Medium |
[electronic resource] / |
Statement of responsibility, etc |
by Beiwei Zhang, Y. F. Li. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
X, 166 p. |
Other physical details |
online resource. |
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
Title |
Intelligent Systems, Control and Automation: Science and Engineering, |
International Standard Serial Number |
2213-8986 ; |
Volume number/sequential designation |
57 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Chapter 1 Introduction -- 1.1 Vision Framework -- 1.2 Background -- 1.2.1 Calibrated Reconstruction -- 1.2.1.1 Static Calibration based methods -- 1.2.1.2 Dynamic Calibration based methods -- 1.2.1.3 Relative Pose Problem -- 1.2.2 Uncalibrated 3D reconstruction -- 1.2.2.1 Factorization-based method -- 1.2.2.2 Stratification-based method -- 1.2.2.3 Using Structured Light System -- 1.3 Scope -- 1.3.1 System Calibration -- 1.3.2 Plane-based Homography -- 1.3.3 Structured Light System -- 1.3.4 Omni-directional Vision System -- 1.4 Objectives -- 1.5 Book Structures -- Chapter 2 System Description -- 2.1 System Introduction -- 2.1.1 Structured Light System -- 2.1.2 Omni-directional Vision System -- 2.2 Component Modeling -- 2.2.1 Convex Mirror -- 2.2.2 Camera Model -- 2.2.3 Projector Model -- 2.3 Pattern Coding Strategy -- 2.3.1 Introduction -- 2.3.2 Color-Encoded Light Pattern -- 2.3.3 Decoding the Light Pattern -- 2.4 Some Preliminaries -- 2.4.1 Notations and Definitions -- 2.4.2 Cross Ratio -- 2.4.3 Plane-based Homography -- 2.4.4 Fundamental Matrix -- Chapter 3 Static Calibration -- 3.1 Calibration Theory -- 3.2 Polygon-based Calibration -- 3.2.1 Design of the planar pattern -- 3.2.2 Solving the vanishing line -- 3.2.3 Solving the projection of a circle -- 3.2.4 Solving the projection of circular point -- 3.2.5 Algorithm -- 3.2.6 Discussion -- 3.3 Intersectant-Circle-based Calibration -- 3.3.1 Planar Pattern Design -- 3.3.2 Solution for the circular point -- 3.4 Concentric-Circle-based Calibration -- 3.4.1 Some Preliminaries -- 3.4.2 The polynomial eigenvalue problem -- 3.4.3 Orthogonality-based Algorithm -- 3.4.4 Experiments -- 3.4.4.1 Numerical Simulations -- 3.4.4.2 Real Image Experiment -- 3.5 Line-based Distortion Correction -- 3.5.1 The distortion model -- 3.5.2 The correction procedure -- 3.5.3 Examples -- 3.6 Summary -- Chapter 4 Homography-based Dynamic Calibration -- 4.1 Problem Statement -- 4.2 System Constraints -- 4.2.1 Two Propositions -- 4.3 Calibration Algorithm -- 4.3.1 Solution for the Scale Factor -- 4.3.2 Solutions for the Translation Vector -- 4.3.3 Solution for Rotation Matrix -- 4.3.4 Implementation Procedure -- 4.4 Error Analyses -- 4.4.1 Errors in the Homographic matrix -- 4.4.2 Errors in the translation vector -- 4.4.3 Errors in the rotation matrix -- 4.5 Experiments Study -- 4.5.1 Computer Simulation -- 4.5.2 Real Data Experiment -- 4.6 Summary -- Chapter 5 3D Reconstruction with Image-to-World Transformation -- 5.1 Introduction -- 5.2 Image-to-World Transformation matrix -- 5.3 Two-Known-Plane based method -- 5.3.1 Static Calibration -- 5.3.2 Determining the on-line Homography -- 5.3.3 Euclidean 3D Reconstruction -- 5.3.4 Configuration of the two scene planes -- 5.3.5 Computational Complexity Study -- 5.3.6 Reconstruction Examples -- 5.4 One-Known-Plane based method -- 5.4.1 Calibration Tasks -- 5.4.2 Generic Homography -- 5.4.3 Dynamic Calibration -- 5.4.4 Reconstruction Procedure -- 5.4.5. Reconstruction Examples -- 5.5 Summary -- Chapter 6 Catadioptric Vision System -- 6.1 Introduction -- 6.1.1 Wide Field-of-View System -- 6.1.2 Calibration of Omni-directional Vision System -- 6.1.3 Test Example -- 6.2 Panoramic Stereoscopic System -- 6.2.1 System Configuration -- 6.2.2 Co-axis Installation -- 6.2.3 System Model -- 6.2.4 Epipolar geometry and 3D reconstruction -- 6.2.5 Calibration Procedure -- 6.2.5.1 Initialization of the Parameters -- 6.2.5.2 Non-linear optimization -- 6.3 Parabolic Camera System -- 6.3.1 System Configuration -- 6.3.2 System Modeling -- 6.3.3 Calibration with Lifted-Fundamental-matrix -- 6.3.3.1 The lifted fundamental matrix -- 6.3.3.2 Calibration Procedure -- 6.3.3.3 Simplified Case -- 6.3.3.4 Discussion -- 6.3.4 Calibration Based on Homographic matrix -- 6.3.4.1 Plane-to-mirror Homography -- 6.3.4.2 Calibration Procedure -- 6.3.4.3 Calibration Test -- 6.3.5 Polynomial Eigenvalue Problem -- 6.3.5.1 Mirror-to-mirror Homography -- 6.3.5.2 Constraints and Solutions -- 6.3.5.3 Test Example -- 6.4 Hyperbolic Camera System -- 6.4.1 System Structure -- 6.4.2 Imaging Process and Back Projection -- 6.4.3 Polynomial Eigenvalue Problem -- 6.5 Summary -- Chapter 7 Conclusions and Future Expectation -- 7.1 Conclusions -- 7.2 Future Expectations -- References. |
520 ## - SUMMARY, ETC. |
Summary, etc |
In this book, the design of two new planar patterns for camera calibration of intrinsic parameters is addressed and a line-based method for distortion correction is suggested. The dynamic calibration of structured light systems, which consist of a camera and a projector is also treated. Also, the 3D Euclidean reconstruction by using the image-to-world transformation is investigated. Lastly, linear calibration algorithms for the catadioptric camera are considered, and the homographic matrix and fundamental matrix are extensively studied. In these methods, analytic solutions are provided for the computational efficiency and redundancy in the data can be easily incorporated to improve reliability of the estimations. This volume will therefore prove valuable and practical tool for researchers and practioners working in image processing and computer vision and related subjects. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
|
Topical term or geographic name as entry element |
Computer vision. |
|
Topical term or geographic name as entry element |
Computer science. |
|
Topical term or geographic name as entry element |
Engineering. |
|
Topical term or geographic name as entry element |
Robotics and Automation. |
|
Topical term or geographic name as entry element |
Image Processing and Computer Vision. |
|
Topical term or geographic name as entry element |
Computational Science and Engineering. |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Li, Y. F. |
Relator term |
author. |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Display text |
Printed edition: |
International Standard Book Number |
9789400726536 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-94-007-2654-3 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
|
Item type |
E-Book |