13 citations · 31 across the 7 of their papers we have counts for
10 papers
Robust Local Optimization Done Right
James Pritts, Kevin Köser
RANSAC scoring and local optimization (LO) impose different robustness requirements, motivating the separation of hypothesis selection from refinement. We systematically isolate th…
BlobBoards: Robust Markers for Accurate Pose
James Pritts, Till Sittart, Hendrik Sauer +4
We propose BlobBoards, a fiducial marker system comprising a dense, multi-scale field of Gaussian blobs and a feature-based pipeline for joint detection, identification, and pose e…
RANSAC Scoring Done Right
James Pritts, Felix Seegräber, Kevin Köser
The most widely used RANSAC variants score candidate models by counting inliers or summing per-point scores that saturate beyond a residual threshold. Every such score requires a u…
BabelCalib: A Universal Approach to Calibrating Central Cameras
Yaroslava Lochman, Kostiantyn Liepieshov, Jianhui Chen +3
Existing calibration methods occasionally fail for large field-of-view cameras due to the non-linearity of the underlying problem and the lack of good initial values for all parame…
Minimal Solvers for Single-View Lens-Distorted Camera Auto-Calibration
Yaroslava Lochman, Oles Dobosevych, Rostyslav Hryniv +1
This paper proposes minimal solvers that use combinations of imaged translational symmetries and parallel scene lines to jointly estimate lens undistortion with either affine recti…
Minimal Solvers for Rectifying from Radially-Distorted Conjugate Translations
James Pritts, Zuzana Kukelova, Viktor Larsson +2
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…