FMAC: a Fair Fiducial Marker Accuracy Comparison Software
This provides a standardized tool for researchers and practitioners in computer vision to evaluate marker-based pose estimation, though it is incremental as it builds on existing rendering and comparison methods.
The paper tackles the problem of fairly comparing pose estimation accuracy for fiducial markers by developing a software that uses synthetic images to analyze errors across 6 degrees of freedom, revealing strengths and weaknesses of well-known markers.
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.