Feature matching is a challenging computer vision task that involves finding
correspondences between two images of a 3D scene. In this paper we consider the dense …

In this survey article, we present interactions between algebraic geometry and computer
vision, which have recently come under the header of algebraic vision. The subject has …

We present an approach to solving hard geometric optimization problems in the RANSAC
framework. The hard minimal problems arise from relaxing the original geometric …

We present novel solutions to previously unsolved problems of relative pose estimation from
images whose calibration parameters, namely focal lengths and radial distortion, are …

We propose a novel approach to estimate the fundamental matrix from point
correspondences and their relative depths. Relative depths can be approximated from the …

This paper proposes a geometric interpretation of the angles and scales which the
orientation-and scale-covariant feature detectors, eg SIFT, provide. Two new general …

Local features eg. SIFT and its affine and learned variants provide region-to-region rather
than point-to-point correspondences. This has recently been exploited to create new …

In this paper we present four cases of minimal solutions for two-view relative pose estimation
by exploiting the affine transformation between feature points and we demonstrate efficient …

We present a complete classification of all minimal problems for generic arrangements of
points and lines completely observed by calibrated perspective cameras. We show that …

We aim at estimating the fundamental matrix in two views from five correspondences of
rotation invariant features obtained by eg the SIFT detector. The proposed minimal solver …