12 Stereo and 3D vision
Chapter status: Structural placeholder.
This chapter currently contains the approved heading structure but no reviewed technical content.
12.1 Two-view geometry
12.1.1 The epipolar constraint
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12.1.2 The essential and fundamental matrices
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12.1.3 Estimation from correspondences
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12.1.4 Stereo rectification
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12.2 Stereo matching
12.2.1 Block-matching costs: SAD, SSD, NCC, census
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12.2.2 Aggregation and disparity selection
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12.2.3 Semi-global matching
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12.2.4 Learned stereo matchers (outline)
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12.2.5 Disparity to depth and triangulation
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12.3 Uncertainty in 3D measurement
12.3.1 Depth-error propagation from disparity
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12.3.2 Task uncertainty versus datasheet accuracy
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12.3.3 Uncertainty budgets for 3D measurement
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12.4 3D imaging modalities
12.4.1 Passive stereo
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12.4.2 Structured-light triangulation and fringe projection
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12.4.3 Time-of-flight cameras
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12.4.4 LiDAR and long-range sensing
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12.4.5 Photogrammetry, structure from motion and MVS
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12.4.6 Comparison and selection guide
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12.5 Point clouds and 3D representations
12.5.1 Point-cloud data structures and file formats
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12.5.2 Filtering, downsampling and normal estimation
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12.5.3 Meshing and surface reconstruction
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12.5.4 Voxelisation and occupancy representations
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12.6 Point-cloud registration and alignment
12.6.1 Iterative closest point (ICP) and variants
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12.6.2 Feature-based 3D registration
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12.6.3 Global alignment strategies
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12.7 3D measurement in practice
12.7.1 Sensor acceptance testing with calibrated artefacts
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12.7.2 Surface interaction: specular and translucent materials
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12.7.3 Warm-up drift and environmental control
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