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Calibration and Orientation of Cameras in Computer Vision 2001 ed. [Kietas viršelis]

Edited by , Edited by
  • Formatas: Hardback, 236 pages, aukštis x plotis: 235x155 mm, weight: 1170 g, XI, 236 p., 1 Hardback
  • Serija: Springer Series in Information Sciences 34
  • Išleidimo metai: 06-Jun-2001
  • Leidėjas: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540652833
  • ISBN-13: 9783540652830
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 236 pages, aukštis x plotis: 235x155 mm, weight: 1170 g, XI, 236 p., 1 Hardback
  • Serija: Springer Series in Information Sciences 34
  • Išleidimo metai: 06-Jun-2001
  • Leidėjas: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3540652833
  • ISBN-13: 9783540652830
Kitos knygos pagal šią temą:
This book was conceived during the Workshop "Calibration and Orientation of Cameras in Computer Vision" at the XVIIth Congress of the ISPRS (In­ ternational Society of Photogrammetry and Remote Sensing), in July 1992 in Washington, D. C. The goal of this workshop was to bring photogrammetry and computer vision experts together in order to exchange ideas, concepts and approaches in camera calibration and orientation. These topics have been addressed in photogrammetry research for a long time, starting in the sec­ ond half of the 19th century. Over the years standard procedures have been developed and implemented, in particular for metric cameras, such that in the photogrammetric community such issues were considered as solved prob­ lems. With the increased use of non-metric cameras (in photogrammetry they are revealingly called "amateur" cameras), especially CCD cameras, and the exciting possibilities of acquiring long image sequences quite effortlessly and processing image data automatically, online and even in real-time, the need to take a new and fresh look at various calibration and orientation issues became obvious. Here most activities emerged through the computer vision commu­ nity, which was somewhat unaware as to what had already been achieved in photogrammetry. On the other hand, photogrammetrists seemed to ignore the new and interesting studies, in particular on the problems of orienta­ tion, that were being performed by computer vision experts.

Recenzijos

From the reviews:









"All you need to know about camera calibration and orientation for close range work is in this book. It certainly is a book for post-graduate students and for those academics supervising them. the editors must be congratulated for bringing together at one point in time most facets of camera calibration and orientation. The list of references at the end of each chapter will be extremely useful for future researchers and this book should adorn the shelves of university libraries." (J. G. Fryer, The Photogrammetric Record, Issue 17, 2002)

Introduction 1(6) Armin Gruen Minimum Solutions for Orientation 7(56) Bernhard P. Wrobel Summary 7(1) Introduction 7(8) Standard Orientation Tasks of Photogrammetry and Computer Vision 15(7) Minimum Solutions for Orientation Using Correspondent Points 22(13) 2D-2D Relative Orientation 22(7) 2D-3D Image Orientation (Space Resection) 29(4) 3D-3D Absolute Orientation 33(2) Uniqueness Conditions of Basic Orientation Tasks 35(19) Representation of Rotation 36(2) The Terms Critical Configurations of First and Second Kind: a Geometrical Interpretation by Two Examples 38(3) Uniqueness Conditions of 2D-2D Relative Orientation 41(7) Uniqueness Conditions of 2D-3D Image Orientation (Space Resection) 48(6) Conclusion 54(9) References 56(7) Generic Estimation Procedures for Orientation with Minimum and Redundant Information 63(32) Wolfgang Forstner Summary 63(1) Motivation 63(2) Problem Statement 65(3) Error Types 66(1) Issues in Error Handling 67(1) Tools 68(18) Quality Assurance 68(2) Instabilities of Estimates or ``How Small is too Small? 70(4) Model Errors or ``How Sensitive is the Result? 74(8) Robust Estimation or ``How to React on Blunders 82(4) Generic Estimation Procedures 86(5) Rules for Choosing Robust Estimation Techniques 86(3) Integrating Robust Estimation and Diagnosis 89(2) Conclusions 91(4) Appendix Algebraic Expression for the Normal Equations of Spatial Resection with Four Parts in Symmetric Position 92(2) References 94(1) Photogrammetric Camera Component Calibration: A Review of Analytical Techniques 95(28) Clive S. Fraser Summary 95(1) Introduction 95(2) Analytical Restitution 97(5) Interior and Exterior Orientation 97(2) Collinearity Equations 99(2) The DLT 101(1) Parameterization of Departures from Collinearity 102(10) Sources of Perturbation 102(1) Radial Distortion 103(2) Decentering Distortion 105(1) Focal Plane Unflatness 106(2) Focal Plane Distortion 108(1) A Practical Model for In-Plane and Out-of-Plane Effects 108(1) Interior Orientation Elements 109(3) Determination of Camera Calibration Parameters 112(6) A General Photogrammetric Model 112(1) Test-Range Calibration 113(1) Self-Calibration 114(2) Distortion Calibration via the Plumbline Technique 116(2) Concluding Remarks 118(5) References 119(4) Least-Squares Camera Calibration Including Lens Distortion and Automatic Editing of Calibration Points 123(14) Donald B. Gennery Summary 123(1) Introduction 123(1) Definition of Camera Model 124(3) Camera Model Without Distortion 124(1) Inclusion of Distortion 125(2) Partial Derivatives 127(1) Adjustment of Camera Model 128(5) Data for Adjustment 128(1) Initialization 129(1) Iterative Solution 130(3) Use of Camera Model 133(4) Projecting from Object Space to Image Space 133(1) Projecting from Image Space to Object Space 134(2) Acknowledgments 136(1) References 136(1) Modeling and Calibration of Variable-Parameter Camera Systems 137(26) Reg G. Willson Steven A. Shafer Summary 137(1) Abstract Camera Models 137(26) Building Multi-Degree-of-Freedom Camera Models 138(11) Applying MDOF Camera Models to Vision Tasks 149(6) A General Theory of Camera Modeling and Calibration 155(5) Acknowledgments 160(1) Reference 161(2) System Calibration Through Self-Calibration 163(32) Armin Gruen Horst A. Beyer Summary 163(1) Introduction 163(1) The Concept of Self-Calibration 164(8) The Bundle Method 164(2) Least Squares Estimation 166(2) Systematic Error Compensation by Self-Calibration 168(2) Treatment of Additional Parameters 170(2) Determinability of Self-Calibration Parameters Under Various Network Conditions 172(8) Final System Test 180(3) Conclusions 183(12) Appendix Algebraic Determinability of Additional Parameters 184(2) Trace Check of Covariance Matrix 186(3) Results of Computational Versions for the Determinability of Additional Parameters 189(4) References 193(2) Self-Calibration of a Stereo Rig from Unknown Camera Motions and Point Correspondences 195(36) Quang-Tuan Luong Olivier D. Faugeras Summary 195(1) Introduction 195(6) The Stereo Calibration Problem 195(2) What do we Mean by Self-Calibration 197(2) An Outline of our Autonomous Approach 199(2) Computing the Fundamental Matrix 201(3) The Fundamental Matrix and the Epipolar Transformation 201(2) A Robust Method for the Determination of the Fundamental Matrix 203(1) Computing the Intrinsic Parameters of the Cameras 204(4) The Principle of the Method 204(1) Kruppa Equations Arising from an Epipolar Transformation 205(1) Kruppa Coefficients and Intrinsic Parameters 206(1) Solving the Kruppa Equations 207(1) Computing the Motion of the Camera 208(5) Two Approaches Based on the Computation of the Fundamental Matrix 208(2) An Experimental Comparison 210(3) Computing the Extrinsic Parameters of a Stereo Rig 213(6) A Direct Approach: Binocular and Trinocular Stereo Rig 215(1) An Indirect, Monocular Approach 216(3) Experimental Results 219(7) An Example of Calibration of a Binocular Stereo Rig 219(6) Reconstructions from a Triplet of Uncalibrated Images Taken by a Camera 225(1) Conclusion 226(5) Acknowledgements 226(1) References 227(4) Index 231