58 research outputs found
Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras
We aim at estimating the fundamental matrix in two views from five
correspondences of rotation invariant features obtained by e.g.\ the SIFT
detector. The proposed minimal solver first estimates a homography from three
correspondences assuming that they are co-planar and exploiting their
rotational components. Then the fundamental matrix is obtained from the
homography and two additional point pairs in general position. The proposed
approach, combined with robust estimators like Graph-Cut RANSAC, is superior to
other state-of-the-art algorithms both in terms of accuracy and number of
iterations required. This is validated on synthesized data and real image
pairs. Moreover, the tests show that requiring three points on a plane is not
too restrictive in urban environment and locally optimized robust estimators
lead to accurate estimates even if the points are not entirely co-planar. As a
potential application, we show that using the proposed method makes two-view
multi-motion estimation more accurate
A Minimal Solution for Two-view Focal-length Estimation using Two Affine Correspondences
A minimal solution using two affine correspondences is presented to estimate
the common focal length and the fundamental matrix between two semi-calibrated
cameras - known intrinsic parameters except a common focal length. To the best
of our knowledge, this problem is unsolved. The proposed approach extends point
correspondence-based techniques with linear constraints derived from local
affine transformations. The obtained multivariate polynomial system is
efficiently solved by the hidden-variable technique. Observing the geometry of
local affinities, we introduce novel conditions eliminating invalid roots. To
select the best one out of the remaining candidates, a root selection technique
is proposed outperforming the recent ones especially in case of high-level
noise. The proposed 2-point algorithm is validated on both synthetic data and
104 publicly available real image pairs. A Matlab implementation of the
proposed solution is included in the paper
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