Metric-Based Evaluation of Fiducial Markers for Medical Procedures

The accurate tracking of patients during a surgery is an essential requirement of computer assisted surgery. Many tracking systems are based on permanently installed infrared camera systems to detect reflective spheres. These tracking concepts need a certain amount of installation effort and are associated with high investments. An alternative are planar fiducial markers, which can be tracked only through RGB data and can therefore be used with different camera systems. The objective of this work is to introduce a set of similarity metrics to compare fiducial markers for pose estimation. We propose eight different similarity metrics to unify the process of evaluation and comparison of marker systems. These are the size and outer margin of the marker, the distance to the camera, the pose estimation accuracy, the runtime of the algorithm, the robustness against external influences, the affection to the sensor system and the number of used markers. We also describe the methodology for evaluating these metrics. We then apply these metrics to compare the ArUco and AprilTag open source marker systems. Our tests conclude that the optical tracking of open source fiducial markers is possible at submillimeter range at distances up to one meter. In addition, the tracking result can be greatly improved by using multiple markers. Accuracy is increased and fluctuations are minimized. The similarity metrics presented by us are suitable for evaluating and comparing marker systems in detail. This can serve as a basis for selecting a suitable system for a specific medical procedure.