Goto

Collaborating Authors

 fiducial tag


Scalable Fiducial Tag Localization on a 3D Prior Map via Graph-Theoretic Global Tag-Map Registration

arXiv.org Artificial Intelligence

Abstract-- This paper presents an accurate and scalable method for fiducial tag localization on a 3D prior environmental map. The proposed method comprises three steps: 1) visual odometry-based landmark SLAM for estimating the relative poses between fiducial tags, 2) geometrical matching-based global tag-map registration via maximum clique finding, and 3) tag pose refinement based on direct camera-map alignment with normalized information distance. Through simulationbased evaluations, the proposed method achieved a 98 % global tag-map registration success rate and an average tag pose estimation accuracy of a few centimeters. Experimental results in a real environment demonstrated that it enables to localize over 110 fiducial tags placed in an environment in 25 minutes for data recording and post-processing. In recent years, map-based visual localization methods have been actively studied and widely used for autonomous navigation systems [1], [2] and user interaction applications Figure 1: With the proposed fiducial tag localization method, (e.g., augmented reality [3]).