Triangulation

Richard Hartley 1 Peter Sturm 2
2 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : In this paper, we consider the problem of finding the position of a point in space given its position in two images taken with cameras with known calibration and pose. This process requires the intersection of two known rays in space, and is commonly known as triangulation. In the absence of noise, this problem is trivial. When noise is present, the two rays will not generally meet, in which case it is necessary to find the best point of intersection. This problem is especially critical in affine and projective reconstruction in which there is no meaningful metric information about the object space. It is desirable to find a triangulation method that is invariant to projective transformations of space. This paper solves that problem by assuming a Gaussian noise model for perturbation of the image coordinates. A non-iterative solution is given that finds a global minimum. Extensive comparisons of the new method with several other methods show that it consistently gives superior results.
Type de document :
Communication dans un congrès
Václav Hlavác and Radim Šára. 6th International Conference on Computer Analysis of Images and Patterns (CAIP '95), Sep 1995, Prague, Czech Republic. Springer-Verlag, 970, pp.190-197, 1995, Lecture Notes in Computer Science (LNCS). 〈http://www.springerlink.com/content/7027546l38383587/〉. 〈10.1007/3-540-60268-2_296〉
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https://hal.inria.fr/inria-00525713
Contributeur : Peter Sturm <>
Soumis le : mardi 12 octobre 2010 - 14:47:33
Dernière modification le : jeudi 11 janvier 2018 - 06:20:04

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Richard Hartley, Peter Sturm. Triangulation. Václav Hlavác and Radim Šára. 6th International Conference on Computer Analysis of Images and Patterns (CAIP '95), Sep 1995, Prague, Czech Republic. Springer-Verlag, 970, pp.190-197, 1995, Lecture Notes in Computer Science (LNCS). 〈http://www.springerlink.com/content/7027546l38383587/〉. 〈10.1007/3-540-60268-2_296〉. 〈inria-00525713〉

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