椭圆
人工智能
计算机视觉
闭塞
计算机科学
生成对抗网络
图像(数学)
数学
几何学
医学
心脏病学
作者
Haodong Bie,Wenjun Xu,Bitao Yao,Jia Cui,Yang Hu
标识
DOI:10.1109/cscwd54268.2022.9776130
摘要
In automated assembly tasks, ellipse detection is usually applied in the vision-based pose estimation of circular workpieces. However, the existing ellipse detection methods cannot effectively solve severe visual occlusion in cluttered environments. To address this problem, this paper proposes a Generative Adversarial Networks (GAN)-supported ellipse detection method against the occlusion condition. The trained GAN network can restore the occluded image of workpieces, so that the elliptical features can be detected robustly. In the experiments with different degrees of occlusion, the ellipse detection rate is above 90%, which shows better performance than other existing methods.
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