Automatic Detection and Fitting of Ellipse Markers Using EllipseNet
Zhengda Qian, Fulin Tang, Bingxi Liu, Yujie Fu, Shaohuan Wu, Xiaohong Jia, Yihong Wu · 2022 26th International Conference on Pattern Recognition (ICPR) · 2022
Ellipses are important elements in projective geometry. Accurate extraction of ellipse information is the first step in many computer vision applications, such as ellipse-based camera calibration and camera pose estimation. At present, most ellipse detection algorithms rely on the edge features extracted by Canny, which leads to a number of wrong detection results since non-ellipse edges features are also involved. To address this problem, this paper proposes a novel ellipse marker detection neural network, called EllipseNet. Notably, we propose a new loss function to enhance the rotation perception ability of EllipseNet. Furthermore, a novel ellipse marker data enhancement method is proposed for saving the time cost of labelling ellipse parameters. Experiments show that EllipseNet can improve the detection precision of ellipse regions by more than 3% improvement compared with other SOTA general object detectors.