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Oguz Kedilioglu,Tomas Marcelo Bocco,Martin Landesberger,Alessandro Rizzo,Jorg Franke 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
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.