Download Accurate Visual Metrology from Single and Multiple by Antonio Criminisi PDF

By Antonio Criminisi

Accurate visible Metrology from unmarried and a number of Uncalibrated Images provides novel suggestions for developing three-d types from bi-dimensional photographs utilizing digital fact instruments. Antonio Criminisi develops the mathematical conception of computing global measurements from unmarried pictures, and builds up a hierarchy of novel, versatile ideas to make measurements and reconstruct third-dimensional scenes from uncalibrated photographs, paying specific realization to the accuracy of the reconstruction.
This ebook contains examples of attention-grabbing attainable purposes (eg. Forensic technological know-how, historical past of artwork, digital truth, Architectural and indoor measurements), offered in an easy method, followed via photos, diagrams and many labored examples to aid the reader comprehend and enforce the algorithms.

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Extra resources for Accurate Visual Metrology from Single and Multiple Uncalibrated Images

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3 Vanishing points and vanishing lines Vanishing points and vanishing lines are extremely powerful geometric cues; they convey a lot of information about the direction of lines and orientation of planes. These entities can be estimated directly from the images and no explicit knowledge of the relative geometry between the camera and the viewed scene is required [21, 78, 84, 114]. Often they lie outside the physical image (as in Fig. 7b), but this does not affect the computations. Straight edges.

P, H) j • the line through two points Xl and X2 is denoted by < XIX2 >. When necessary, further notation conventions will be described in each chapter. 1 Camera models and perspective mappings The image formation process must be modelled in a rigorous mathematical way. This section describes the camera models and the projective transformations which are relevant in the remainder of the book. 1 Pinhole camera model The most general linear camera model is the well-known central projection (pinhole camera).

Note that the predicted ellipse and the simulated one are almost overlapping. These figures are obtained using parameters related to a real situation. 4 for a homographic mapping between two generic planes, using synthetic data. Increasing the number of computation points. 4b shows what happens if the number of computation points used to estimate the homography matrix increases. Six ellipses are drawn, three have been predicted by the analytical theory and another three obtained from the Monte Carlo test.

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