Close-Range Photogrammetry and 3D Imaging

Chapter 1: Introduction

• • 1.1 Overview
• • 1.1.1 Content
• • 1.1.2 References
• • 1.2 Fundamental methods
• • 1.2.1 The photogrammetric process
• • 1.2.2 Aspects of photogrammetry
• • 1.2.3 Image-forming model
• • 1.2.4 Photogrammetric systems and procedures
• • 1.2.4.1 Digital system
• • 1.2.4.2 Recording and analysis procedures
• • 1.2.5 Photogrammetric products
• • 1.3 Application areas
• • 1.4 Historical development

Chapter 2: Mathematical fundamentals

• • 2.1 Coordinate systems
• • 2.1.1 Pixel and sensor coordinate system
• • 2.1.2 Image and camera coordinate systems
• • 2.1.3 Model coordinate system
• • 2.1.4 Object coordinate system
• • 2.2 Coordinate transformations
• • 2.2.1 Plane transformations
• • 2.2.1.1 Homogenous coordinates
• • 2.2.1.2 Similarity transformation
• • 2.2.1.3 Affine transformation
• • 2.2.1.4 Polynomial transformation
• • 2.2.1.5 Bilinear transformation
• • 2.2.1.6 Projective transformation
• • 2.2.2 Spatial rotations
• • 2.2.2.1 Rotation matrix using trigonometric functions
• • 2.2.2.2 Rotation matrix using quaternions
• • 2.2.2.3 Rodrigues rotation matrix
• • 2.2.2.4 Rotation matrix with direction cosines
• • 2.2.2.5 Normalization of rotation matrices
• • 2.2.2.6 Comparison of coefficients
• • 2.2.3 Spatial transformations
• • 2.2.3.1 General transformations
• • 2.2.3.2 Central projection
• • 2.2.3.3 General affine transformation
• • 2.2.4 Spatial similarity transformation
• • 2.2.4.1 Mathematical model
• • 2.2.4.2 Approximate values
• • 2.2.4.3 Calculation with eigenvalues and quaternions
• • 2.2.5 Additional coordinate transformations
• • 2.2.5.1 Spherical coordinates
• • 2.2.5.2 Cylindrical coordinates
• • 2.3 Geometric elements
• • 2.3.1 Analytical geometry in the plane
• • 2.3.1.1 Straight line
• • 2.3.1.2 Circle
• • 2.3.1.3 Ellipse
• • 2.3.1.4 Curves
• • 2.3.2 Analytical geometry in 3D space
• • 2.3.2.1 Straight line
• • 2.3.2.2 Plane
• • 2.3.2.3 Rotationally symmetric shapes
• • 2.3.3 Surfaces
• • 2.3.3.1 Digital surface model
• • 2.3.3.2 Digital volume model (voxel)
• • 2.3.3.3 Range images
• • 2.3.3.4 B-spline and Bézier surfaces
• • 2.4 Adjustment techniques
• • 2.4.1 The problem
• • 2.4.1.1 Functional model
• • 2.4.1.2 Stochastic model
• • 2.4.2 Least-squares method (Gauss-Markov linear model)
• • 2.4.2.1 Adjustment of direct observations
• • 2.4.2.2 General least squares adjustment
• • 2.4.2.3 Levenberg-Marquardt algorithm
• • 2.4.2.4 Conditional least squares adjustment
• • 2.4.3 Quality measures
• • 2.4.3.1 Accuracy measures
• • 2.4.3.2 Confidence interval
• • 2.4.3.3 Correlations
• • 2.4.3.4 Reliability
• • 2.4.3.5 Precision of calculated coordinates
• • 2.4.4 Error detection in practice
• • 2.4.4.1 Error detection without adjustment
• • 2.4.4.2 Data snooping
• • 2.4.4.3 Variance component estimation
• • 2.4.4.4 Robust estimation with weighting functions
• • 2.4.4.5 Robust estimation according to L1 norm
• • 2.4.4.6 RANSAC
• • 2.4.5 Computational aspects
• • 2.4.5.1 Linearization
• • 2.4.5.2 Normal systems of equations
• • 2.4.5.3 Sparse matrix techniques and optimization

Chapter 4: Analytical methods

• • 4.1 Overview
• • 4.2 Processing of single images
• • 4.2.1 Exterior orientation
• • 4.2.1.1 Standard case
• • 4.2.1.2 Special case of terrestrial photogrammetry
• • 4.2.2 Collinearity equations
• • 4.2.3 Space resection
• • 4.2.3.1 Space resection with known interior orientation
• • 4.2.3.2 Space resection with unknown interior orientation
• • 4.2.3.3 Approximate values for resection
• • 4.2.3.4 Resection with minimum object information
• • 4.2.3.5 Quality measures
• • 4.2.4 Linear orientation methods
• • 4.2.4.1 Direct linear transformation (DLT)
• • 4.2.4.2 Perspective projection matrix
• • 4.2.5 Object position and orientation (pose) by inverse resection
• • 4.2.5.1 Position and orientation of an object with respect to a camera
• • 4.2.5.2 Position and orientation of one object relative to another
• • 4.2.6 Projective transformation of a plane
• • 4.2.6.1 Mathematical model
• • 4.2.6.2 In

Chapter 5: Digital image analysis

Chapter 6: Measuring tasks and systems

Chapter 7: Measurement design and quality

Chapter 8: Example applications

Chapter 9: Literature