Score: 1

FMAC: a Fair Fiducial Marker Accuracy Comparison Software

Published: January 12, 2026 | arXiv ID: 2601.07723v1

By: Guillaume J. Laurent, Patrick Sandoz

Potential Business Impact:

Tests how well robots see objects in 3D.

Business Areas:
Facial Recognition Data and Analytics, Software

This paper presents a method for carrying fair comparisons of the accuracy of pose estimation using fiducial markers. These comparisons rely on large sets of high-fidelity synthetic images enabling deep exploration of the 6 degrees of freedom. A low-discrepancy sampling of the space allows to check the correlations between each degree of freedom and the pose errors by plotting the 36 pairs of combinations. The images are rendered using a physically based ray tracing code that has been specifically developed to use the standard calibration coefficients of any camera directly. The software reproduces image distortions, defocus and diffraction blur. Furthermore, sub-pixel sampling is applied to sharp edges to enhance the fidelity of the rendered image. After introducing the rendering algorithm and its experimental validation, the paper proposes a method for evaluating the pose accuracy. This method is applied to well-known markers, revealing their strengths and weaknesses for pose estimation. The code is open source and available on GitHub.

Repos / Data Links

Page Count
20 pages

Category
Computer Science:
CV and Pattern Recognition