DETERMINING THE EPIPOLAR GEOMETRY AND ITS UNCERTAINTY A REVIEW PDF

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: It captures all geometric information contained in two images, and its determination is very important in many applications such as scene modeling and vehicle navigation.

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We'd like to understand how you use our websites in order to improve them. Register your interest. It captures all geometric information contained in two images, and its determination is very important in many applications such as scene modeling and vehicle navigation.

This paper gives an introduction to the epipolar geometry, and provides a complete review of the current techniques for estimating the fundamental matrix and its uncertainty.

A well-founded measure is proposed to compare these techniques. Projective reconstruction is also reviewed. The software which we have developed for this review is available on the Internet. This is a preview of subscription content, log in to check access. Aggarwal, J. On the computation of motion from sequences of images-A review.

In Proc. IEEE , Vol. Aloimonos, J. Perspective approximations. Image and Vision Computing , 8 3 Anderson, T. An Introduction to Multivariate Statistical Analysis. Ayache, N. Artificial Vision for Mobile Robots. MIT Press. Ayer, S. Segmentation of moving objects by robust motion parameterestimation over multiple frames.

Eklundh Ed. II, pp. Google Scholar. Beardsley, P. Navigation using affine structure from motion. Boufama, B. Epipole and fundamental matrix estimation using the virtual parallax property.

Carlsson, S. Multiple image invariance using the double algebra. Mundy, A. Zissermann, and D. Forsyth Eds. Csurka, G. Characterizing the uncertainty of the fundamental matrix. Computer Vision and Image Understanding , 68 1 , Deriche, R.

Robust recovery of the epipolar geometry for an uncalibrated stereo rig. Enciso, R. Auto-calibration des capteurs visuels actifs. Reconstruction 3D active.

Faugeras, O. What can be seen in three dimensions with an uncalibrated stereo rig. Sandini Ed. The MIT Press. Stratification of 3-D vision: Projective, affine, and metric representations.

Journal of the Optical Society of America A , 12 3 Motion and structure from motion in a piecewise planar environment. Camera selfcalibration: Theory and experiments. What can two images tell us about a third one?. On the geometry and algebra of the point and line correspondences between n images. Fischler, M. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography.

Communications of the ACM , Golub, G. Matrix Computations. The John Hopkins University Press. Haralick, R. Computer vision theory: The lack thereof. Computer Vision, Graphics, and Image Processing , Hartley, R. Euclidean reconstruction from uncalibrated views. Mundy and A. Zisserman Eds. Projective reconstruction and invariants from multiple images.

In defence of the 8-point algorithm. Stereo from uncalibrated cameras. Heeger, D. Subspace methods for recovering rigid motion I: Algorithm and implementation. The International Journal of Computer Vision , 7 2 Hesse, O. Reine Angew. Huang, T. Motion and structure from feature correspondences: A review. IEEE , 82 2 Huber, P. Robust Statistics. Laveau, S. Longuet-Higgins, H.

A computer algorithm for reconstructing a scene from two projections. Nature , Luong, Q. Canonic representations for the geometries of multiple projective views. The fundamental matrix: Theory, algorithms and stability analysis. The International Journal of Computer Vision , 1 17 Maybank, S.

Theory of Reconstruction from Image Motion. A theory of self-calibration of a moving camera. The International Journal of Computer Vision , 8 2 Mohr, R. Accurate projective reconstruction.

Relative 3d reconstruction using multiple uncalibrated images. More, J. The levenberg-marquardt algorithm, implementation and theory. In Numerical Analysis , G. Watson Ed. Mundy, J. Geometric Invariance in Computer Vision.

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