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.
ArUcoE: Enhanced ArUco Marker / Kedilioglu, O.; Bocco, T.; Landesberger, M.; Rizzo, A.; Franke, J.. - ELETTRONICO. - (2021). (Intervento presentato al convegno 21st International Conference on Control, Automation and Systems (ICCAS 2021) tenutosi a Jeju, Republic of Korea nel 12-15 Oct. 2021) [10.23919/ICCAS52745.2021.9650050].
ArUcoE: Enhanced ArUco Marker
A. Rizzo;
2021
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.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2957666