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Application of Ghost-DeblurGAN to Fiducial Marker Detection. (arXiv:2109.03379v3 [eess.IV] CROSS LISTED)
March 4, 2022, 2:12 a.m. | Yibo Liu, Amaldev Haridevan, Hunter Schofield, Jinjun Shan
cs.LG updates on arXiv.org arxiv.org
Feature extraction or localization based on the fiducial marker could fail
due to motion blur in real-world robotic applications. To solve this problem, a
lightweight generative adversarial network, named Ghost-DeblurGAN, for
real-time motion deblurring is developed in this paper. Furthermore, on account
that there is no existing deblurring benchmark for such task, a new large-scale
dataset, YorkTag, is proposed that provides pairs of sharp/blurred images
containing fiducial markers. With the proposed model trained and tested on
YorkTag, it is demonstrated …
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