Search Results for author: Levente Hajder

Found 7 papers, 1 papers with code

Fast Globally Optimal Surface Normal Estimation from an Affine Correspondence

no code implementations ICCV 2023 Levente Hajder, Lajos Lóczi, Daniel Barath

The proposed approach provides a new globally optimal solution for this over-determined problem and proves that it reduces to a linear system that can be solved extremely efficiently.

Surface Normal Estimation Visual Localization

Finding Geometric Models by Clustering in the Consensus Space

1 code implementation CVPR 2023 Daniel Barath, Denys Rozumny, Ivan Eichhardt, Levente Hajder, Jiri Matas

Dominant instances are found via a RANSAC-like sampling and a consolidation process driven by a model quality function considering previously proposed instances.

Clustering Motion Estimation +1

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

no code implementations13 Aug 2020 Istan Gergo Gal, Daniel Barath, Levente Hajder

For the first class of solvers, the sought plane is expected to be perpendicular to one of the camera axes.

Pose Estimation

Automatic Estimation of Sphere Centers from Images of Calibrated Cameras

no code implementations24 Feb 2020 Levente Hajder, Tekla Tóth, Zoltán Pusztai

Calibration of devices with different modalities is a key problem in robotic vision.

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

no code implementations13 Dec 2019 Levente Hajder, Daniel Barath

A new minimal solver is proposed for the semi-calibrated case, i. e. the camera parameters are known except a common focal length.

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

no code implementations13 Dec 2019 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.

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

no code implementations CVPR 2017 Daniel Barath, Tekla Toth, Levente Hajder

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.

Vocal Bursts Valence Prediction

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