Panoramic Imaging Sensor-Line Cameras and Laser Range-Finders
by Huang, Fay; Klette, Reinhard; Scheibe , KarstenEdition: 1st
Format: Hardcover
Pub. Date: 2008-11-17
Publisher(s): Wiley
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Summary
Panoramic imaging is a progressive application and research area. This technology has applications in digital photography, robotics, film productions for panoramic screens, architecture, environmental studies, remote sensing and GIS technology. Applications demand different levels of accuracy for 3D documentation or visualizations. This book describes two modern technologies for capturing high-accuracy panoramic images and range data, namely the use of sensor-line cameras and laser range-finders. It provides mathematically accurate descriptions of the geometry of these sensing technologies and the necessary information required to apply them to 3D scene visualization or 3D representation. The book is divided into three parts: Part One contains a full introduction to panoramic cameras and laser range-finders, including a discussion of calibration to aid preparation of equipment ready for use. Part Two explains the concept of stereo panoramic imaging, looking at epipolar geometry, spatial sampling, image quality control and camera analysis and design. Part Three looks at surface modelling and rendering based on panoramic input data, starting with the basics and taking the reader through to more advanced techniques such as the optimization of surface meshes and data fusion. There is also an accompanying website containing high-resolution visual samples and animations, illustrating techniques discussed in the text. Panoramic Imaging is primarily aimed at researchers and students in engineering or computer science involved in using imaging technologies for 3D visualization or 3D scene reconstruction. It is also of significant use as an advanced manual to practising engineers in panoramic imaging. In brief, the book is of value to all those interested in current developments in multimedia imaging technology
Author Biography
Fay Huang, Institute of Computer Science and Information Engineering, National Ilan University, Taiwan Reinhard Klette, Department of Computer Science, The University of Auckland, New Zealand Karsten Scheibe, German Aerospace Center (DLR), Germany
Table of Contents
| Preface | p. xi |
| Series Preface | p. xv |
| Website and Exercises | p. xvii |
| List of Symbols | p. xix |
| Introduction | p. 1 |
| Panoramas | p. 1 |
| Accurate Panoramic Imaging | p. 1 |
| Importance of Panoramas | p. 2 |
| Panoramic Paintings | p. 3 |
| Chinese Scrolls | p. 4 |
| European Panoramic Paintings | p. 5 |
| Panoramic or Wide-Angle Photographs | p. 6 |
| Historic Panoramic Cameras | p. 6 |
| Photogrammetry | p. 7 |
| Digital Panoramas | p. 9 |
| Image Mosaicing | p. 9 |
| Panoramas by Stitching | p. 10 |
| Catadioptric Panoramas | p. 12 |
| Stereo Panoramic Imaging | p. 14 |
| Striving for Accuracy | p. 14 |
| A General Perspective on Panoramic Sensors | p. 14 |
| Rotating Sensor-Line Cameras | p. 15 |
| Laser Range-Finder | p. 18 |
| Exercises | p. 20 |
| Further Reading | p. 20 |
| Cameras and Sensors | p. 23 |
| Camera Models | p. 23 |
| Capturing Surface and Central Point | p. 23 |
| Pinhole Camera | p. 24 |
| Ideal Pinhole Camera | p. 25 |
| Sensor-Matrix Cameras | p. 27 |
| Sensor-Line Cameras | p. 27 |
| Optics | p. 29 |
| Waves and Rays of Light; Law of Refraction | p. 29 |
| Ideal Gaussian Optics | p. 29 |
| Pupil, Aperture, and f-Number | p. 31 |
| Relation to the Pinhole Camera | p. 32 |
| Sensor Models | p. 34 |
| Rotating Sensor-Line Cameras | p. 34 |
| Rotating Multi-Line Cameras | p. 40 |
| Rotating Sensor-Matrix Cameras | p. 41 |
| Laser Range-Finder | p. 43 |
| Examples and Challenges | p. 46 |
| Exercises | p. 48 |
| Further Reading | p. 48 |
| Spatial Alignments | p. 49 |
| Mathematical Fundamentals | p. 49 |
| Euclidean Spaces and Coordinate Systems | p. 49 |
| 2D Manifolds and Surface Normals | p. 53 |
| Vectors, Matrices, and Affine Transforms | p. 55 |
| Central Projection: World into Image Plane | p. 58 |
| Symmetric Perspective Projections | p. 58 |
| Asymmetric Perspective Projections | p. 58 |
| Classification of Panoramas | p. 59 |
| Views and Projection Centers | p. 59 |
| Refined Classification | p. 60 |
| Coordinate Systems for Panoramas | p. 63 |
| Planar Capturing Surface | p. 63 |
| Spherical Capturing Surfaces | p. 65 |
| Cylindrical Capturing Surfaces | p. 65 |
| Geometric Projection Formula for Cylindrical Panorama | p. 66 |
| Rotating Cameras | p. 70 |
| Image Vectors and Projection Rays | p. 70 |
| Single-Center Panorama (Ideal Case) | p. 72 |
| Multi-Center Panorama with [omega] = 0 | p. 73 |
| Multi-Center Panorama with [omega] [not equal] 0 | p. 73 |
| General Case of a Rotating Sensor-Line Camera | p. 74 |
| Mappings between Different Image Surfaces | p. 75 |
| Reprojection onto a Straight Cylinder | p. 75 |
| Cylindrical Panorama onto Sphere | p. 77 |
| Cylindrical Panorama onto Tangential Plane | p. 77 |
| Laser Range-Finder | p. 78 |
| Exercises | p. 79 |
| Further Reading | p. 80 |
| Epipolar Geometry | p. 81 |
| General Epipolar Curve Equation | p. 81 |
| Constrained Poses of Cameras | p. 89 |
| Leveled Panoramic Pair | p. 89 |
| Co-axial Panoramic Pair | p. 95 |
| Symmetric Panoramic Pair | p. 96 |
| Exercises | p. 97 |
| Further Reading | p. 98 |
| Sensor Calibration | p. 99 |
| Basics | p. 99 |
| Camera Calibration | p. 99 |
| Extrinsic and Intrinsic Parameters | p. 101 |
| Registration and Calibration | p. 102 |
| Preprocesses for a Rotating Sensor-Line Camera | p. 103 |
| Precalibration | p. 103 |
| Correction of Color Shift | p. 106 |
| Radiometric Corrections | p. 110 |
| Geometric Corrections | p. 110 |
| Correction of Mechanical Vibrations | p. 112 |
| A Least-Square Error Optimization Calibration Procedure | p. 113 |
| Collinearity Equations | p. 113 |
| Difference between Planar Capturing Surface and Panoramic Cylinder | p. 115 |
| Parameters and Objective Functions | p. 116 |
| General Error Criterion | p. 117 |
| Discussion | p. 119 |
| Geometric Dependencies of R and [omega] | p. 120 |
| Three Methods | p. 120 |
| Focal Length and Central Row | p. 121 |
| Point-based Approach | p. 124 |
| Image Correspondence Approach | p. 125 |
| Parallel-line-based Approach | p. 129 |
| Experimental Results | p. 135 |
| Error Components in LRF Data | p. 138 |
| LRF Used in Experiments | p. 138 |
| Error Measurement | p. 138 |
| Exercises | p. 143 |
| Further Reading | p. 144 |
| Spatial Sampling | p. 145 |
| Stereo Panoramas | p. 145 |
| Sampling Structure | p. 145 |
| Outward Case | p. 146 |
| Inward Case | p. 149 |
| Spatial Resolution | p. 152 |
| Indexing System | p. 152 |
| Computation of Resolution | p. 155 |
| Distances between Spatial Samples | p. 157 |
| Basic Definitions | p. 157 |
| Horizontal Sample Distance | p. 159 |
| Vertical Sample Distance | p. 162 |
| Depth Sample Distance | p. 163 |
| Exercises | p. 165 |
| Further Reading | p. 166 |
| Image Quality Control | p. 167 |
| Two Requirements | p. 167 |
| Terminology | p. 169 |
| Range of Interest in the Scene | p. 169 |
| Distance to Target Range | p. 170 |
| Depth, Disparity, and Angular Disparity | p. 171 |
| Image Resolution | p. 173 |
| Parameter Optimization | p. 175 |
| Off-Axis Distance R and Principal Angle [omega] | p. 175 |
| Examples | p. 179 |
| Error Analysis | p. 181 |
| Definitions and Notation | p. 181 |
| Parameter Dependencies | p. 181 |
| Error in the Distance to Inner Border of RoI | p. 182 |
| Error in the Distance to Outer Border of RoI | p. 184 |
| Error in the Distance to Target Range | p. 186 |
| Exercises | p. 188 |
| Further Reading | p. 189 |
| Sensor Analysis and Design | p. 191 |
| Introduction | p. 191 |
| Scene Composition Analysis | p. 192 |
| Simplifications, Main Focus, and Layout | p. 192 |
| Geometric Analysis | p. 193 |
| Algebraic Analysis | p. 197 |
| Stereoacuity Analysis | p. 201 |
| Geometric Analysis | p. 201 |
| Algebraic Analysis | p. 206 |
| Specification of Camera Parameters | p. 209 |
| Analysis of Scene Ranges | p. 209 |
| Specification of Off-Axis Distance R | p. 211 |
| Specification of Principal Angle [omega] | p. 212 |
| Exercises | p. 214 |
| Further Reading | p. 215 |
| 3D Meshing and Visualization | p. 217 |
| 3D Graphics | p. 217 |
| The Graphics Pipeline | p. 217 |
| Central Projection | p. 219 |
| Orthogonal Projection | p. 220 |
| Stereo Projection | p. 221 |
| Surface Modeling | p. 222 |
| Triangulation | p. 222 |
| Creating a Digital Surface Model | p. 223 |
| Bump Mapping | p. 224 |
| Improving Triangulated Surfaces | p. 226 |
| Delaunay Triangulation | p. 227 |
| More Techniques for Dealing with Digital Surfaces | p. 228 |
| Basic Filters | p. 228 |
| Fast Connectivity | p. 228 |
| Detection and Darning of Holes | p. 230 |
| Detection of Planar Surface Patches | p. 231 |
| Edge Estimation and Edge Correction | p. 233 |
| Exercises | p. 235 |
| Further Reading | p. 236 |
| Data Fusion | p. 237 |
| Determination of Camera Image Coordinates | p. 237 |
| Single-Projection-Center Panoramas | p. 238 |
| Multi-Projection-Center Panoramas with [omega] = 0 | p. 239 |
| Multi-Projection-Center Panoramas with [omega] [not equal] 0 | p. 239 |
| General Case | p. 242 |
| Texture Mapping | p. 243 |
| High Resolution Orthophotos | p. 246 |
| Fusion of Panoramic Images and Airborne Data | p. 247 |
| Airborne Cameras | p. 248 |
| Rectifying Airborne Images and Generation of DSMs | p. 250 |
| Mapping of Terrestrial Side-View Images | p. 251 |
| Mapping of Perspective Airborne Images | p. 253 |
| Exercises | p. 255 |
| Further Reading | p. 255 |
| References | p. 257 |
| Index | p. 263 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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