Download e-book for iPad: Accurate Visual Metrology from Single and Multiple by Antonio Criminisi

By Antonio Criminisi

ISBN-10: 0857293273

ISBN-13: 9780857293275

ISBN-10: 1447110404

ISBN-13: 9781447110408

Accurate visible Metrology from unmarried and a number of Uncalibrated Images offers novel innovations for developing third-dimensional types from bi-dimensional pictures utilizing digital truth instruments. Antonio Criminisi develops the mathematical thought of computing global measurements from unmarried pictures, and builds up a hierarchy of novel, versatile strategies to make measurements and reconstruct 3-dimensional scenes from uncalibrated pictures, paying specific recognition to the accuracy of the reconstruction.
This booklet contains examples of fascinating potential purposes (eg. Forensic technological know-how, heritage of artwork, digital truth, Architectural and indoor measurements), awarded in an easy method, followed by means of photographs, diagrams and lots of labored examples to assist 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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2 Computing uncertainties There may be errors in the world and image points used to compute the homography, and there may be errors in the image points back-projected to make world measurements. All of these sources of uncertainty must be taken into account in order to compute a cumulative uncertainty for the world measurement (cf. Fig. 2). In this section, formulae to compute the uncertainty for planar measurements under various error situations are developed. The first order analysis is assumed sufficient.

This section lists the formulae used to compute the uncertainty for measurements under various error situations. The first order analysis is assumed sufficient. The uncertainty in the homography is computed as described in the previous section. Notation. New notation is introduced here to simplify the formulae. 10) In the following we will determine the 3 x 3 covariance matrix Ax of the homogeneous world point X. The conversion to a 2 x 2 covariance matrix A;(2 for inhomogeneous coordinates is given by: A~x2 = V fAx V fT where X = (X, Y, W)T and: Vf = IjW (Wo W-Y 0 -X) 2 f is the function mapping homogeneous to inhomogeneous coordinates.

7. Homology mapping of points from one plane to a parallel one, the two planes being related in the world by a parallel projection. a Original image, the floor and the top of the filing cabinet are parallel planes. b Their common vanishing line (axis of the homology, shown in white) has been computed by intersecting two sets of horizontal edges. The vertical vanishing point (vertex of the homology) has been computed by intersecting vertical edges. c Two reference corresponding points rand r' are selected on the two planes and the characteristic ratio of the homology computed.

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Accurate Visual Metrology from Single and Multiple Uncalibrated Images by Antonio Criminisi

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