Search Results for author: James Pritts

Found 8 papers, 6 papers with code

Minimal Solvers for Single-View Lens-Distorted Camera Auto-Calibration

2 code implementations17 Nov 2020 Yaroslava Lochman, Oles Dobosevych, Rostyslav Hryniv, James Pritts

This paper proposes minimal solvers that use combinations of imaged translational symmetries and parallel scene lines to jointly estimate lens undistortion with either affine rectification or focal length and absolute orientation.

Camera Auto-Calibration Scene Labeling

Minimal Solvers for Rectifying from Radially-Distorted Conjugate Translations

1 code implementation4 Nov 2019 James Pritts, Zuzana Kukelova, Viktor Larsson, Yaroslava Lochman, Ondřej Chum

This paper introduces minimal solvers that jointly solve for radial lens undistortion and affine-rectification using local features extracted from the image of coplanar translated and reflected scene texture, which is common in man-made environments.

Minimal Solvers for Rectifying from Radially-Distorted Scales and Change of Scales

1 code implementation25 Jul 2019 James Pritts, Zuzana Kukelova, Viktor Larsson, Yaroslava Lochman, Ondřej Chum

The proposed solvers use the affine invariant that coplanar repeats have the same scale in rectified space.

Rectification from Radially-Distorted Scales

1 code implementation16 Jul 2018 James Pritts, Zuzana Kukelova, Viktor Larsson, Ondrej Chum

This paper introduces the first minimal solvers that jointly estimate lens distortion and affine rectification from repetitions of rigidly transformed coplanar local features.

Radially-Distorted Conjugate Translations

1 code implementation CVPR 2018 James Pritts, Zuzana Kukelova, Viktor Larsson, Ondrej Chum

The solvers are derived from constraints induced by the conjugate translations of an imaged scene plane, which are integrated with the division model for radial lens distortion.

Coplanar Repeats by Energy Minimization

no code implementations26 Nov 2017 James Pritts, Denys Rozumnyi, M. Pawan Kumar, Ondrej Chum

This paper proposes an automated method to detect, group and rectify arbitrarily-arranged coplanar repeated elements via energy minimization.

Detection, Rectification and Segmentation of Coplanar Repeated Patterns

no code implementations CVPR 2014 James Pritts, Ondrej Chum, Jiri Matas

This paper presents a novel and general method for the detection, rectification and segmentation of imaged coplanar repeated patterns.

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