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Computer Science > Robotics

arXiv:2108.02555 (cs)
[Submitted on 5 Aug 2021]

Title:DeepScanner: a Robotic System for Automated 2D Object Dataset Collection with Annotations

Authors:Valery Ilin, Ivan Kalinov, Pavel Karpyshev, Dzmitry Tsetserukou
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Abstract:In the proposed study, we describe the possibility of automated dataset collection using an articulated robot. The proposed technology reduces the number of pixel errors on a polygonal dataset and the time spent on manual labeling of 2D objects. The paper describes a novel automatic dataset collection and annotation system, and compares the results of automated and manual dataset labeling. Our approach increases the speed of data labeling 240-fold, and improves the accuracy compared to manual labeling 13-fold. We also present a comparison of metrics for training a neural network on a manually annotated and an automatically collected dataset.
Comments: Accepted to 26th International Conference on Emerging Technologies and Factory Automation (ETFA) 2021, IEEE copyright, 8 pages, 10 figures
Subjects: Robotics (cs.RO); Machine Learning (cs.LG)
Cite as: arXiv:2108.02555 [cs.RO]
  (or arXiv:2108.02555v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2108.02555

Submission history

From: Valery Ilin [view email]
[v1] Thu, 5 Aug 2021 12:21:18 UTC (7,381 KB)
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