Multiple View Geometry in Computer Vision

Introduction - a tour of multiple view geometry
Part 0. The Background: Projective Geometry, Transformations and Estimation:
Projective geometry and transformations of 2D
Projective geometry and transformations of 3D
Estimation - 2D projective transforms
Algorithm evaluation and error analysis
Part 1. Camera Geometry and Single View Geometry:
Camera models
Computation of the camera matrix
More single view geometry
Part 2. Two-View Geometry:
Epipolar geometry and the fundamental matrix
3D reconstruction of cameras and structure
Computation of the fundamental matrix F
Structure computation
Scene planes and homographies
Affine epipolar geometry
Three-View Geometry:
The trifocal tensor
Computation of the trifocal tensor T
N -View Geometry:
N-linearities and multiple view tensors
N-view computational methods
Auto-calibration
Duality
Chirality
Degenerate configurations
Appendices:
Appendix 1 - Tensor Notation
Appendix 2 - Gaussian (Normal) and χ2 Distributions
Appendix 3 - Parameter Estimation
Appendix 4 - Matrix Properties and Decompositions
Appendix 5 - Least-squares Minimization
Appendix 6 - Iterative Estimation Methods
Appendix 7 - Some Special Plane Projective Transformations