Luhmann T., Robson S., Kyle S., Boehm J. / Лухман Т., Робсон С., Кийл С., Боем Ян - Close-Range Photogrammetry and 3D Imaging / Фотограмметрия Близкого Расстояния и 3D-Визуализация (4th ed. / 4-е изд.) [2023, PDF, ENG]

1 Introduction-1
1.1         Overview 1
1.1.1       Content--1
1.1.2       References 2
1.2         Fundamental methods 2
1.2.1       The photogrammetric process 2
1.2.2       Aspects of photogrammetry 4
1.2.3       Image-forming model 7
1.2.4       Photogrammetric systems and procedures--10
1.2.4.1     Digital system 10
1.2.4.2     Recording and analysis procedures--12
1.2.5       Photogrammetric products 14
1.3         Application areas 15
1.4         Historical development 18
2 Mathematical fundamentals 32
2.1     Coordinate systems 32
2.1.1   Pixel and sensor coordinate system---32
2.1.2   Image and camera coordinate systems--33
2.1.3   Model coordinate system 34
2.1.4   Object coordinate system-35
2.2     Coordinate transformations 36
2.2.1   Plane transformations 36
2.2.1.1 Homogenous coordinates - 36
2.2.1.2 Similarity transformation 37
2.2.1.3 Affine transformation 38
2.2.1.4 Polynomial transformation 39
2.2.1.5 Bilinear transformation 40
2.2.1.6 Projective transformation--41
2.2.2   Spatial rotations 44
2.2.2.1 Rotation matrix using trigonometric functions--44
2.2.2.2 Rotation matrix using quaternions 47
2.2.2.3 Rodrigues rotation matrix--50
2.2.2.4 Rotation matrix with direction  cosines--50
2.2.2.5 Normalization of rotation matrices 50
2.2.2.6 Comparison of coefficients 51
2.2.3   Spatial transformations 52
2.2.3.1 General transformations 52
2.2.3.2 Central projection - 54
2.2.3.3 General affine transformation-55
2.2.4   Spatial similarity transformation-56
2.2.4.1 Mathematical model-56
2.2.4.2 Approximate values-58
2.2.4.3 Calculation with eigenvalues and quaternions-61
2.2.5   Additional coordinate transformations-62
2.2.5.1 Spherical coordinates-62
2.2.5.2 Cylindrical coordinates-63
2.3     Geometric elements-63
2.3.1   Analytical geometry in the plane-65
2.3.1.1 Straight line-65
2.3.1.2 Circle-68
2.3.1.3 Ellipse-69
2.3.1.4 Curves-72
2.3.2   Analytical geometry in 3D space-76
2.3.2.1 Straight line-76
2.3.2.2 Plane-79
2.3.2.3 Rotationally symmetric shapes-82
2.3.3   Surfaces-87
2.3.3.1 Digital surface model-88
2.3.3.2 Digital volume model (voxel)-90
2.3.3.3 Range images-90
2.3.3.4 B-spline and Bezier surfaces-92
2.4     Adjustment techniques-93
2.4.1   The problem-93
2.4.1.1 Functional model-93
2.4.1.2 Stochastic model - 95
2.4.2   Least-squares method (Gauss-Markov linear model)-96
2.4.2.1 Adjustment of direct observations-96
2.4.2.2 General least squares adjustment-97
2.4.2.3 Levenberg-Marquardt algorithm-99
2.4.2.4 Conditional least squares adjustment-100
2.4.3   Quality measures-101
2.4.3.1 Accuracy measures-102
2.4.3.2 Confidence interval-104
2.4.3.3 Correlations-106
2.4.3.4 Reliability-107
2.4.3.5 Precision of calculated coordinates-111
2.4.4   Error detection in practice-112
2.4.4.1 Error detection without adjustment-114
2.4.4.2 Data snooping-114
2.4.4.3 Variance component estimation-114
2.4.4.4 Robust estimation with weighting functions-115
2.4.4.5 Robust estimation according to L1 norm-116
2.4.4.6 RANSAC-117
2.4.5   Computational aspects-118
2.4.5.1 Linearization-118
2.4.5.2 Normal systems of equations-118
2.4.5.3 Sparse matrix techniques and optimization-119
3       Imaging technology-121
3.1     Physics of image formation-121
3.1.1   Wave optics-121
3.1.1.1 Electro-magnetic spectrum-121
3.1.1.2 Radiometry-122
3.1.1.3 Refraction and reflection-123
3.1.1.4 Diffraction-125
3.1.1.5 Polarization-127
3.1.2   Optical imaging-128
3.1.2.1 Geometric optics-128
3.1.2.2 Apertures and stops-130
3.1.2.3 Focussing-131
3.1.2.4 Scheimpflug condition-134
3.1.3   Aberrations-135
3.1.3.1 Distortion-136
3.1.3.2 Chromatic aberration-137
3.1.3.3 Spherical aberration-138
3.1.3.4 Astigmatism and curvature of field-139
3.1.3.5 Light fall-off and vignetting-140
3.1.4   Aspherical lenses-141
3.1.5   Resolution-143
3.1.5.1 Resolving power of a lens-143
3.1.5.2 Geometric resolving power-144
3.1.5.3 Contrast and modulation transfer function-145
3.1.6   Fundamentals of sampling theory-147
3.1.6.1 Sampling theorem-147
3.1.6.2 Detector characteristics-149
3.2     Photogrammetric imaging concepts-151
3.2.1   Offline and online systems-151
3.2.1.1 Offline photogrammetry-152
3.2.1.2 Online photogrammetry-152
3.2.2   Imaging configurations-153
3.2.2.1 Single image acquisition-153
3.2.2.2 Stereo image acquisition-153
3.2.2.3 Multi-image acquisition-154
3.3     Geometry of the camera as a measuring device-155
3.3.1   Image scale and accuracy-155
3.3.1.1 Image scale-155
3.3.1.2 Accuracy estimation-158
3.3.2   Interior orientation of a camera-159
3.3.2.1 Physical definition of the image coordinate system-160
3.3.2.2 Perspective centre and distortion-161
3.3.2.3 Parameters of interior orientation-163
3.3.2.4 Metric and semi-metric cameras-165
3.3.2.5 Determination of interior orientation (calibration)-166
3.3.3   Standardized correction functions-168
3.3.3.1 Radial distortion-168
3.3.3.2 Tangential distortion-173
3.3.3.3 Affinity and shear-174
3.3.3.4 Total correction-175
3.3.4   Alternative correction formulations-176
3.3.4.1 Simplified models-176
3.3.4.2 Additional parameters-176
3.3.4.3 Correction of distortion as a function of object distance-178
3.3.4.4 Image-variant calibration-180
3.3.4.5 Correction of local image deformations-181
3.3.4.6 Chromatic aberration-183
3.3.5   Iterative correction of imaging errors-184
3.3.6   Transformation of interior orientation parameters-186
3.3.7   Fisheye projections-187
3.4     System components-189
3.4.1   Opto-electronic imaging sensors-191
3.4.1.1 Principle of CCD sensor-191
3.4.1.2 CCD area sensors-193
3.4.1.3 CMOS matrix sensors-195
3.4.1.4 Sensor formats-196
3.4.1.5 Microlenses-198
3.4.1.6 Colour cameras-198
3.4.1.7 Sensor architecture-202
3.4.1.8 Geometric properties-202
3.4.1.9 Radiometric properties-205
3.4.2   Camera technology-208
3.4.2.1 Camera types - 208
3.4.2.2 Shutter-211
3.4.2.3 Image stabilization and cleaning-214
3.4.2.4 Sensor to lens flange distance-215
3.4.3   Lenses-215
3.4.3.1 Relative aperture and f/number-215
3.4.3.2 Field of view-216
3.4.3.3 Image circle and sensor format-217
3.4.3.4 Super wide-angle and fisheye lenses-218
3.4.3.5 Zoom lenses-219
3.4.3.6 Tilt-shift lenses-220
3.4.3.7 Telecentric lenses-222
3.4.3.8 Reflective optics-223
3.4.3.9 Stereo image splitting-224
3.4.4   Filters-225
3.5     Imaging systems-226
3.5.1   Industrial cameras-226
3.5.2   Digital cameras-228
3.5.3   High-speed cameras-232
3.5.4   Stereo and multi-camera systems-235
3.5.5   Micro and macro-scanning cameras-237
3.5.5.1 Micro scanning-237
3.5.5.2 Macro scanning-238
3.5.6   Panoramic cameras-240
3.5.6.1 Line scanners-240
3.5.6.2 Panorama stitching-241
3.5.6.3 Panoramas from fisheye lenses-243
3.5.7   Endoscopes-244
3.5.8   Thermal imaging cameras-245
3.5.9   Multi-spectral and hyperspectral cameras-246
3.5.9.1 Multi-spectral cameras-246
3.5.9.2 Hyperspectral cameras-247
3.6     Reflection and illumination-249
3.6.1   Reflection models-249
3.6.1.1 Reflection types-249
3.6.1.2 Retro-reflection-251
3.6.2   High contrast photogrammetric targeting-252
3.6.2.1 Retro-reflective targets-252
3.6.2.2 Other target materials-254
3.6.3   Illumination and projection techniques-255
3.6.3.1 Electronic flash-255
3.6.3.2 Pattern projection - 257
3.6.3.3 Laser projectors-258
3.6.3.4 Directional lighting-259
3.6.3.5 Reflectance Transformation Imaging-261
4       Analytical methods-263
4.1     Overview-263
4.2     Processing of single images-265
4.2.1   Exterior orientation-265
4.2.1.1 Standard case-265
4.2.1.2 Special case of terrestrial photogrammetry-267
4.2.2   Collinearity equations-268
4.2.3   Space resection-272
4.2.3.1 Space resection with known interior orientation-273
4.2.3.2 Space resection with unknown interior orientation-275
4.2.3.3 Approximate values for resection-276
4.2.3.4 Resection with minimum object information-276
4.2.3.5 Quality measures-279
4.2.4   Linear orientation methods-280
4.2.4.1 Direct linear transformation (DLT)-280
4.2.4.2 Perspective projection matrix-282
4.2.5   Object position and orientation (pose) by inverse resection-284
4.2.5.1 Position and orientation of an object with respect to a camera-284
4.2.5.2 Position and orientation of one object relative to another-284
4.2.6   Projective transformation of a plane-287
4.2.6.1 Mathematical model-287
4.2.6.2 Influence of interior orientation-290
4.2.6.3 Influence of non-coplanar object points-290
4.2.6.4 Measurement of flat objects-291
4.2.7   Monoplotting-292
4.2.7.1 Standard geometric shapes (geometric primitives)-292
4.2.7.2 Digital surface models-293
4.2.8   Rectification-295
4.2.8.1 Plane rectification-295
4.2.8.2 Differential rectification (orthophotos)-296
4.2.8.3 Image mosaics-301
4.3     Processing of stereo images-303
4.3.1   Stereoscopic principle-303
4.3.1.1 Stereoscopic matching-303
4.3.1.2 Tie points-304
4.3.1.3 Orientation of stereo image pairs-305
4.3.1.4 Normal case of stereo photogrammetry-306
4.3.2   Epipolar geometry-307
4.3.3   Relative orientation-309
4.3.3.1 Coplanarity constraint-311
4.3.3.2 Calculation-312
4.3.3.3 Model coordinates-313
4.3.3.4 Calculation of epipolar lines-314
4.3.3.5 Calculation of normal-case images (epipolar images)-315
4.3.3.6 Quality of relative orientation-317
4.3.3.7 Special cases of relative orientation-319
4.3.4   Fundamental matrix and essential matrix-321
4.3.5   Absolute orientation-323
4.3.5.1 Mathematical model-323
4.3.5.2 Definition of the datum-325
4.3.5.3 Calculation of exterior orientations-325
4.3.5.4 Calculation of relative orientation from exterior orientations-325
4.3.6   Stereoscopic processing-326
4.3.6.1 Principle of stereo image processing-326
4.3.6.2 Point determination using image coordinates-328
4.3.6.3 Point determination with floating mark-334
4.4     Multi-image processing and bundle adjustment-336
4.4.1   General remarks-336
4.4.1.1 Objectives-336
4.4.1.2 Development-337
4.4.1.3 Data flow - 339
4.4.2   Mathematical model-341
4.4.2.1 Adjustment model-341
4.4.2.2 Normal equations-343
4.4.2.3 Combined adjustment of photogrammetric and survey observations-347
4.4.2.4 Adjustment of additional parameters-351
4.4.3   Object coordinate system (definition of datum)-353
4.4.3.1 Rank and datum defect-353
4.4.3.2 Reference points-355
4.4.3.3 Direct georeferencing-358
4.4.3.4 Free net adjustment-358
4.4.4   Generation of approximate values-362
4.4.4.1 Strategies for the automatic calculation of approximate values-364
4.4.4.2 Initial value generation by automatic point measurement-368
4.4.4.3 Practical aspects of the generation of approximate values-369
4.4.5   Quality measures and analysis of results-371
4.4.5.1 Output report-371
4.4.5.2 Sigma 0 and reprojection error-371
4.4.5.3 Precision of image coordinates-372
4.4.5.4 Precision of object coordinates-373
4.4.5.5 Quality of self-calibration-374
4.4.6   Strategies for bundle adjustment-376
4.4.6.1 Simulation-376
4.4.6.2 Divergence 377
4.4.6.3 Elimination of gross errors 378
4.4.7   Multi-image calculation of points and geometric elements 378
4.4.7.1 General spatial intersection--379
4.4.7.2 Direct determination of geometric elements--381
4.5     Panoramic photogrammetry---382
4.5.1   Cylindrical panoramic imaging model 382
4.5.2   Orientation of panoramic imagery 385
4.5.2.1 Approximate values 385
4.5.2.2 Space resection 386
4.5.2.3 Bundle adjustment - 386
4.5.3   Epipolar geometry - 387
4.5.4   Spatial intersection 389
4.5.5   Rectification of panoramic images - 389
4.5.5.1 Orthogonal rectification - 389
4.5.5.2 Tangential images - 390
4.6     Multi-media photogrammetry 391
4.6.1   Light refraction at media interfaces 391
4.6.1.1 Media interfaces 391
4.6.1.2 Plane parallel media interfaces 392
4.6.1.3 Spherical media interfaces--395
4.6.1.4 Ray tracing through refracting interfaces--396
4.6.2   Extended model of bundle triangulation--398
4.6.2.1 Object-invariant interfaces--398
4.6.2.2 Bundle-invariant interfaces--399
4.6.3   Special aspects of underwater photogrammetry--400
5 Digital image analysis 402
5.1     Fundamentals 402
5.1.1   Image processing procedure--402
5.1.2   Pixel coordinate system 404
5.1.3   Handling image data 405
5.1.3.1 Image pyramids - 405
5.1.3.2 Data formats - 406
5.1.3.3 Image compression - 409
5.1.3.4 Video formats 410
5.1.3.5 Integral images - 411
5.2     Image pre-processing - 413
5.2.1   Point operations - 413
5.2.1.1 Histogram - 413
5.2.1.2 Lookup tables 414
5.2.1.3 Contrast enhancement - 415
5.2.1.4 Thresholding-417
5.2.1.5 Image arithmetic-419
5.2.2   Colour operations-420
5.2.2.1 Colour spaces-420
5.2.2.2 Colour transformations-423
5.2.2.3 Colour calibration-426
5.2.2.4 Colour combinations-427
5.2.3   Filter operations-429
5.2.3.1 Spatial domain and frequency domain-429
5.2.3.2 Smoothing filters-432
5.2.3.3 Morphological operations-434
5.2.3.4 Wallis filter-436
5.2.4   Edge extraction-438
5.2.5   First order differential filters-439
5.2.5.1 Second order differential filters-441
5.2.5.2 Laplacian of Gaussian filter-442
5.2.5.3 Image sharpening-443
5.2.5.4 Hough transform-444
5.2.5.5 Enhanced edge operators-445
5.2.5.6 Sub-pixel interpolation-447
5.3     Geometric image transformation-450
5.3.1   Fundamentals of rectification-451
5.3.2   Grey value interpolation-452
5.3.3   Textured images-455
5.3.3.1 Texture mapping-455
5.3.3.2 Synthetic images-457
5.4     Digital processing of single images-457
5.4.1   Approximate values-458
5.4.1.1 Possibilities-458
5.4.1.2 Segmentation of point features-458
5.4.2   Measurement of single point features-460
5.4.2.1 On-screen measurement-460
5.4.2.2 Centroid methods-460
5.4.2.3 Correlation methods-462
5.4.2.4 Least-squares matching-464
5.4.2.5 Structural measuring methods-469
5.4.2.6 Accuracy issues-472
5.4.3   Feature extraction-473
5.4.3.1 Interest operators and feature detectors-473
5.4.3.2 Forstner operator-474
5.4.3.3 SUSAN operator-476
5.4.3.4 FAST operator-477
5.4.3.5 SIFT operator-478
5.4.3.6 SURF Operator-481
5.4.3.7 ORB operator-481
5.5     Image matching and 3D object reconstruction-482
5.5.1   Overview-482
5.5.2   Strategies for matching non-oriented images-486
5.5.2.1 Coded targets-486
5.5.2.2 Structure-from-motion-486
5.5.2.3 Image masking-488
5.5.3   Similarity measures-489
5.5.3.1 Sums of differences-490
5.5.3.2 Census and Hamming distance-490
5.5.3.3 Hashing-491
5.5.3.4 Normalized cross-correlation-492
5.5.3.5 Least-squares matching-492
5.5.3.6 Euclidian distance between feature vectors-492
5.5.4   Correspondence analysis based on epipolar geometry-493
5.5.4.1 Matching in image pairs-493
5.5.4.2 Semi-global matching-495
5.5.5   Multi-image matching-499
5.5.5.1 Multi-View Stereo-499
5.5.5.2 Matching in oriented image triples-499
5.5.5.3 Matching in an unlimited number of images-502
5.5.5.4 Multi-image least-squares matching-502
5.5.6   Matching methods with object models-507
5.5.6.1 Object-based multi-image matching-507
5.5.6.2 Multi-image matching with surface grids-511
5.5.6.3 Object-based semi-global multi-image matching (OSGM)-513
5.5.6.4 Additional object-based matching methods-516
5.5.7   Matching in image sequences-519
5.5.7.1 2D object tracking in single-camera sequences-520
5.5.7.2 Target tracking-520
5.5.7.3 3D object reconstruction from single-camera image sequences-523
5.5.7.4 Object tracking in multi-camera image sequences-524
5.5.7.5 Prediction of subsequent points (Kalman filter)-525
5.5.7.6 Simultaneous Localization and Mapping (SLAM)-527
6 Measuring tasks and systems-529
6.1     Overview-529
6.2     Targeting-529
6.2.1   Target designs-530
6.2.1.1 Circular targets-530
6.2.1.2 Spherical targets-532
6.2.1.3 Patterned targets - 534
6.2.1.4 Coded targets-534
6.2.2   Target systems-536
6.2.2.1 Centring targets-536
6.2.2.2 Probes - 536
6.2.2.3 Hidden-point devices-537
6.2.2.4 6DOF targets-539
6.3     Realization of reference systems-540
6.3.1   References-540
6.3.1.1 Definition of scale-540
6.3.1.2 Definition of reference coordinate systems-542
6.3.2   Measurement systems-543
6.3.2.1 Video total stations and multistations-543
6.3.2.2 Laser trackers-544
6.4     Interactive multi-image processing systems-546
6.4.1   Programs with CAD functionality-546
6.4.2   Structure-from-motion programs-548
6.4.3   Offline processing systems for industrial applications-549
6.4.4   Educational software-550
6.5     Tactile probing systems-552
6.5.1   Measurement principle-552
6.5.2   Single-camera systems-553
6.5.2.1 Camera with hand-held probe-553
6.5.2.2 Probing system with integrated camera-554
6.5.3   Stereo and multi-camera systems-555
6.6     Industrial measuring systems for single point features-557
6.6.1   Mobile industrial point measuring-systems-557
6.6.1.1 Offline photogrammetric systems-557
6.6.1.2 Online photogrammetric systems-559
6.6.1.3 Stereo vision systems-562
6.6.2   Static industrial online measuring systems-564
6.6.2.1 Tube inspection system-565
6.6.2.2 Steel-plate positioning system-566
6.6.2.3 Multi-camera system with projected point arrays-567
6.7     Systems for surface measurement-568
6.7.1   Overview-568
6.7.1.1 Active and passive systems-568
6.7.1.2 Surface textures for area-based measurement-569
6.7.2   Laser triangulation-571
6.7.3   Fringe projection systems-571
6.7.3.1 Stationary fringe projection-571
6.7.3.2  Dynamic fringe projection (phase-shift method)-573
6.7.3.3  Coded light (Gray code)-574
6.7.3.4  Aperiodic fringe projection-575
6.7.3.5  Single-camera fringe-projection systems-576
6.7.3.6  Multi-camera fringe-projection systems-578
6.7.4    Point and grid projection-580
6.7.4.1  Multi-camera systems with target grid projection-580
6.7.4.2  Multi-camera system with grid projection-581
6.7.4.3  Multi-camera system with regular etched patterns-582
6.7.5    Systems utilizing random patterns-582
6.7.5.1  Dual-camera system with projection of random patterns-  583
6.7.5.2  Surface measurement with textured adhesive film-584
6.7.5.3  Measurement of dynamic surface change-584
6.7.6    Range cameras-587
6.7.6.1  Kinect-587
6.7.6.2  Current generation range cameras-589
6.7.6.3  Light-field cameras-590
6.8      Laser-scanning systems-591
6.8.1    3D laser scanners-591
6.8.2    2D and 1D laser scanning-598
6.8.3    Panoramic imaging systems with laser distance measurement-599
6.9      Registration and orientation of images and scans-600
6.9.1    Multi-image photogrammetry-601
6.9.2    Orientation with object points-602
6.9.2.1  Orientation with unknown reference targets-602
6.9.2.2  Orientation with known reference targets-603
6.9.2.3  Orientation with known feature points-604
6.9.3    Scanner location by optical tracking-604
6.9.4    Mechanical location of scanners-606
6.9.5    Orientation with external systems and reference points- 607
6.9.6    Connecting point clouds (registration)-609
6.9.6.1  Registration with 3D reference targets-609
6.9.6.2  Iterative closest point (ICP)-610
6.9.7    ICP-based scanner devices-612
6.10     Dynamic photogrammetry-612
6.10.1   Relative movement between object and imaging system- 613
6.10.1.1 Static object-613
6.10.1.2 Moving object-615
6.10.2   Recording dynamic sequences-616
6.10.2.1 Camera system for robot calibration-616
6.10.2.2 High-speed 6 DOF system-617
6.10.2.3 Recording with high-speed cameras-618
6.10.2.4 Particle Image Velocimetry-619
6.10.3   Motion capture (MoCap)-620
6.11     Mobile measurement platforms-621
6.11.1   Mobile mapping systems-621
6.11.1.1 Outdoor mapping-621
6.11.1.2 Indoor mapping-622
6.11.2   Close-range aerial imagery-624
6.11.2.1 Aerial systems - 624
6.11.2.2 Sensor technology-626
6.11.2.3 Flight planning-628
6.11.2.4 Photogrammetric processing-631
6.12     Visualisation systems-633
6.12.1   Digital stereo viewing systems-633
6.12.2   AR/VR systems-635
6.12.2.1 VR systems-635
6.12.2.2 AR/MR systems-636
6.12.3   Industrial 3D projection systems-637
7 Measurement design and quality-639
7.1      Project planning-639
7.1.1    Planning criteria-639
7.1.2    Accuracy issues-640
7.1.3    Restrictions on imaging configuration-641
7.1.4    Accuracy estimation by simulation-644
7.1.4.1  Variance-covariance propagation-644
7.1.4.2  Monte Carlo simulation-646
7.1.4.3  Unscented transformation-649
7.1.4.4  Bootstrap simulation-650
7.1.5    Design of the imaging configuration-651
7.1.5.1  Network design-651
7.1.5.2  Scale-653
7.2      Quality measures and performance testing-655
7.2.1    Statistical parameters-656
7.2.1.1  Precision and accuracy parameters from a bundle adjustment-656
7.2.1.2  Accuracy-657
7.2.1.3  Relative accuracy-658
7.2.2    Metrological parameters - 658
7.2.2.1  Measurement uncertainty-658
7.2.2.2  Reference value-659
7.2.2.3  Measurement error-660
7.2.2.4  Accuracy-660
7.2.2.5  Precision - 660
7.2.2.6  Tolerance 661
7.2.2.7  Resolution 662
7.2.3    Acceptance and re-verification of measuring systems 662
7.2.3.1  Definition of terms 663
7.2.3.2  Differentiation from coordinate measuring machines (CMMs) 665
7.2.3.3  Reference artefacts 666
7.2.3.4  Testing of point-by-point measuring systems 667
7.2.3.5  Testing of area-scanning systems 671
7.3      Strategies for camera calibration 675
7.3.1    Calibration methods 675
7.3.1.1  Test-field calibration 676
7.3.1.2  Plumb-line calibration 679
7.3.1.3  On-the-job calibration 680
7.3.1.4  Self-calibration 680
7.3.1.5  System calibration - 681
7.3.2    Imaging configurations - 682
7.3.2.1  Calibration using a plane point field - 682
7.3.2.2  Calibration using a spatial point field 683
7.3.2.3  Calibration with moving scale bar 684
7.3.3    Calibration of multi-camera and non-standard imaging systems 685
7.3.3.1  Calibration of stereo and multi-camera systems 685
7.3.3.2  Calibration of fisheye cameras---------685
7.3.3.3  Calibration of underwater cameras 687
7.3.4    Quality criteria for camera calibration 687
7.3.5    Problems with self-calibration 688
8 Example applications 693
8.1     Architecture, archaeology and cultural heritage 693
8.1.1   Photogrammetric building records 693
8.1.1.1 Drawings 695
8.1.1.2 3D building models 696
8.1.1.3 Image plans and orthophotos 696
8.1.2   Examples of photogrammetric building reconstructions 697
8.1.2.1 Torhaus Seedorf 697
8.1.2.2 The Milan Cathedral 698
8.1.2.3 Lurji monastery 700
8.2     Cultural heritage artefacts 702
8.2.1   Art and museum pieces 702
8.2.1.1 Statues and sculptures 702
8.2.1.2 Death mask of pharaoh Tutankhamun 703
8.2.1.3 Sarcophagus of the Spouses 704
8.2.1.4 Goethe elephant skull-706
8.2.2   Archaeological recordings-707
8.2.2.1 3D record of Pompeii-707
8.2.2.2 Temple of Hadrian-708
8.2.2.3 Otzing burial chamber-710
8.2.2.4 Survey of the Bremen cog-711
8.2.2.5 Megalithic tomb Kleinenkneten-713
8.3     3D city and landscape models-715
8.3.1   City models-715
8.3.2   Generation of terrain models from multi-spectral image data-716
8.3.3   Landscape model from laser scanning and photogrammetry-718
8.4     Engineering surveying and civil engineering-719
8.4.1   3D modelling of complex objects-719
8.4.1.1 As-built documentation-719
8.4.1.2 Building Information Modelling-720
8.4.1.3 Stairwell measurement-722
8.4.2   Deformation analysis-723
8.4.2.1 Deformation of concrete tanks-723
8.4.2.2 Measurement of wind-turbine rotor blades-724
8.4.3   Material testing-727
8.4.3.1 Surface measurement of mortar joints in brickwork-727
8.4.3.2 Structural loading tests-728
8.4.4   Roof and fagade measurement-730
8.5     Industrial applications-731
8.5.1   Power stations and production plants-731
8.5.1.1 Wind power stations-731
8.5.1.2 Particle accelerators-734
8.5.2   Aerospace industry-735
8.5.2.1 Inspection of tooling jigs-735
8.5.2.2 Production control-736
8.5.2.3 Visual checking-736
8.5.2.4 Antenna measurement-737
8.5.3   Car industry-738
8.5.3.1 Rapid prototyping and reverse engineering-739
8.5.3.2 Car safety tests - 740
8.5.3.3 Car body deformations-742
8.5.4   Ship building industry-743
8.6     Underwater photogrammetry-744
8.6.1   Measurement of water and other fluid surfaces-744
8.6.2   Underwater measurement of welds-746
8.6.3   Underwater photogrammetry of the Costa Concordia shipwreck-748
8.7     Medicine 749
8.7.1   Surface measurement 750
8.7.2   Online navigation systems 751
8.8     Miscellaneous applications--753
8.8.1   Forensic applications 753
8.8.1.1 Accident recording 753
8.8.1.2 Scene-of-crime recording - 754
8.8.1.3 Anthropological analyses - 756
8.8.2   Scientific applications - 756
8.8.2.1 Monitoring glacier movements 757
8.8.2.2 Earth sciences 758
8.8.2.3 Entomology 760
8.8.2.4 Measurement of a soap bubble--761
9 Literature 763
9.0 Textbooks 763
9.0.1       Photogrammetry 763
9.0.2       Optic, camera and imaging techniques 763
9.0.3       Digital image processing, computer vision and pattern recognition 764
9.0.4       Mathematics and 3D computer graphics-764
9.0.5       Least-squares adjustment and statistics 764
9.0.6       Industrial, optical 3D metrology, quality control 765
9.0.7       Applications 765
9.1 Chapter 1 - Introduction and history 765
9.2 Chapter 2 - Mathematical fundamentals 767
9.2.1       Transformations and geometry--767
9.2.2       Adjustment techniques 767
9.3 Chapter 3 - Imaging technology--768
9.3.1       Optics and sampling theory--768
9.3.2       Camera modelling and calibration--769
9.3.3       Sensors and cameras 771
9.3.4       Target materials and illumination 772
9.4 Chapter 4 - Analytical methods--772
9.4.1       Analytical photogrammetry 772
9.4.2       Bundle adjustment 773
9.4.3       Multi-media photogrammetry 774
9.4.4       Panoramic photogrammetry---776
9.5 Chapter 5 - Digital image analysis--776
9.5.1       Fundamentals 776
9.5.2       Pattern recognition and image matching 776
9.6 Chapter 6 - Measurement tasks and systems---779
9.6.1       Target and reference systems 779
9.6.2       Interactive measuring and processing systems 780
9.6.3       Measurement of points and contours 781
9.6.4       Laser-scanning systems 781
9.6.5       Measurement of surfaces 782
9.6.6       Range and 3D cameras - 782
9.6.7       Registration and orientation - 783
9.6.8       Dynamic and mobile systems - 783
9.7 Chapter 7 - Quality issues and optimization 784
9.7.1       Project planning and simulation 784
9.7.2       Quality 785
9.7.3       Camera calibration - 786
9.8 Chapter 8 - Applications - 787
9.8.1       Architecture, archaeology, city models 787
9.8.2       Engineering and industrial applications 789
9.8.3       Underwater photogrammetry 790
9.8.4       Medicine, forensics, earth sciences 791
9.9 Other sources of information 792
9.9.1       Standards and guidelines 792
9.9.2       Working groups and conferences 792
Abbreviations 795
Image sources 799
Index 803