activity
20172020
most citedA Minimal Solution for Two-view Focal-length Estimation using Two Affine Correspondences

2 citations · 2 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2020

Pose Estimation for Vehicle-mounted Cameras via Horizontal and Vertical Planes

Istan Gergo Gal, Daniel Barath, Levente Hajder

We propose two novel solvers for estimating the egomotion of a calibrated camera mounted to a moving vehicle from a single affine correspondence via recovering special homographies…

cs.CV2020

Making Affine Correspondences Work in Camera Geometry Computation

Daniel Barath, Michal Polic, Wolfgang Förstner +3

Local features e.g. 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 min…

cs.CV2019

Relative planar motion for vehicle-mounted cameras from a single affine correspondence

Levente Hajder, Daniel Barath

Two solvers are proposed for estimating the extrinsic camera parameters from a single affine correspondence assuming general planar motion. In this case, the camera movement is con…

cs.CV2019

Least-squares Optimal Relative Planar Motion for Vehicle-mounted Cameras

Levente Hajder, Daniel Barath

A new closed-form solver is proposed minimizing the algebraic error optimally, in the least-squares sense, to estimate the relative planar motion of two calibrated cameras. The mai…

cs.CV2019

Homography from two orientation- and scale-covariant features

Daniel Barath, Zuzana Kukelova

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

cs.CV20172 cited

A Minimal Solution for Two-view Focal-length Estimation using Two Affine Correspondences

Daniel Barath, Tekla Toth, Levente Hajder

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 intrinsi…