Accurate Visual Metrology from Single and Multiple Uncalibrated Images presents novel techniques for constructing three-dimensional models from bi-dimensional images using virtual reality tools. Antonio Criminisi develops the mathematical theory of computing world measurements from single images, and builds up a hierarchy of novel, flexible techniques to make measurements and reconstruct three-dimensional scenes from uncalibrated images, paying particular attention to the accuracy of the reconstruction.
This book includes examples of interesting viable applications (eg. Forensic Science, History of Art, Virtual Reality, Architectural and indoor measurements), presented in a simple way, accompanied by pictures, diagrams and plenty of worked examples to help the reader understand and implement the algorithms.

1. Introduction.- 1.1 Accurate measurements from images.- 1.2 Why use vision.- 1.3 Why is visual metrology hard.- 1.4 Applications and examples.- 1.5 Summary.- 2.Related work.- 2.1 Using one view.- 2.2 Using two views.- 2.3 Using three or more views.- 2.4 Partial calibration.- 2.5 Parallax-based approaches.- 2.6 Investigation of accuracy.- 2.7 Projective geometry and history of art.- Background geometry and notation.- 3.1 Camera models and perspective mappings.- 3.2 Radial distortion correction.- 3.3 Vanishing points and vanishing lines.- 3.4 Uncertainty analysis.- Metrology on planes.- 4.1 Estimating the homography.- 4.2 Uncertainty analysis.- 4.3 Application - a plane measuring device.- 4.4 Duality and homologies.- 5. Single-view metrology.- 5.1 Geometry.- 5.2 Algebraic representation.- 5.3 Uncertainty analysis.- 5.4 Three-dimensional metrology from a single view.- 5.5 Applications.- 5.6 Missing base point.- 6. Metrology from planar parallax.- 6.1 Background.- 6.2 Geometry and duality.- 6.3 Scene reconstruction.- 6.4 Uncertainty analysis.- Gallery of examples.- 7.1 Reconstruction from photographs.- 7.2 Reconstruction from paintings.- 7.3 Discussion.- 8. Conclusion.- 8.1 Summary.- 8.2 Discussion.- 8.3 Future work.- A. Metrology on planes, computing uncertainty in the homography.- B. Maximum likelihood estimation of end points for isotropic uncertainties.- C. Single-view metrology, variance of distance between planes.- C.1 Covariance of maximum likelihood estimation (MLE) end points.- D. Single-view metrology, variance of the affine parameter ?.- E. Metrology from planar parallax, derivations.- E.1 Computing the motion constraints.- E.2 Computing distances of points from planes directly in the images.- F. Metrology from planar parallax, variance of distances.- F.1Definitions.- References.