ArUcoE: Enhanced ArUco Marker

Kedilioglu O, Bocco TM, Landesberger M, Rizzo A, Franke J (2021)

Publication Type: Conference contribution, Original article

Publication year: 2021

Original Authors: Oguz Kedilioglu, Tomas Marcelo Bocco, Martin Landesberger, Alessandro Rizzo, Jorg Franke

Conference Proceedings Title: IEEE

Event location: Jeju KR

DOI: 10.23919/ICCAS52745.2021.9650050

Abstract

This paper presents a novel fiducial marker type called ArUcoE. It is obtained from a standard ArUco marker by enhancing it with a chessboard-like pattern. With our approach the pose estimation accuracy of any ArUco marker can easily be increased. Further methods to increase the accuracy are analyzed. By applying a subpixel algorithm to the corner regions we are able to locate the corner points within a pixel and overcome the restriction of pixel-level accuracy. A deep-learning-based super-resolution method is used to artificially increase the pixel density in the same regions. Additionally, the effect of using a single and a stereo camera setup on the accuracy is shown.

Authors with CRIS profile

Oguz Kedilioglu Lehrstuhl für Fertigungsautomatisierung und Produktionssystematik Jörg Franke Lehrstuhl für Fertigungsautomatisierung und Produktionssystematik

Involved external institutions

Politecnico di Torino IT Italy (IT) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Kedilioglu, O., Bocco, T.M., Landesberger, M., Rizzo, A., & Franke, J. (2021). ArUcoE: Enhanced ArUco Marker. In IEEE. Jeju, KR.

MLA:

Kedilioglu, Oguz, et al. "ArUcoE: Enhanced ArUco Marker." Proceedings of the 2021 21st International Conference on Control, Automation and Systems (ICCAS), Jeju 2021.

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