Detail publikace

Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans

GAJDOŠECH, L. KOCUR, V. STUCHLÍK, M. HUDEC, L. MADARAS, M.

Originální název

Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

An automated robotic system needs to be as robust as possible and fail-safe in general while having relatively high precision and repeatability. Although deep learning-based methods are becoming research standard on how to approach 3D scan and image processing tasks, the industry standard for processing this data is still analytically-based. Our paper claims that analytical methods are less robust and harder for testing, updating, and maintaining. This paper focuses on a specific task of 6D pose estimation of a bin in 3D scans. Therefore, we present a high-quality dataset composed of synthetic data and real scans captured by a structured-light scanner with precise annotations. Additionally, we propose two different methods for 6D bin pose estimation, an analytical method as the industrial standard and a  baseline data-driven method. Both approaches are cross-evaluated, and our experiments show that augmenting the training on real scans with synthetic data improves our proposed data-driven neural model. This position paper is preliminary, as proposed methods are trained and evaluated on a relatively small initial dataset which we plan to extend in the future.

Klíčová slova

Computer Vision, Bin Pose Estimation, 6D Pose Estimation, Deep Learning, Point Clouds

Autoři

GAJDOŠECH, L.; KOCUR, V.; STUCHLÍK, M.; HUDEC, L.; MADARAS, M.

Vydáno

6. 2. 2022

Nakladatel

SciTePress - Science and Technology Publications

Místo

Setubal

ISBN

978-989-758-555-5

Kniha

Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP

Strany od

545

Strany do

552

Strany počet

8

URL

https://www.scitepress.org/Link.aspx?doi=10.5220/0010878200003124

BibTex

@inproceedings{BUT182954,
  author="Lukáš {Gajdošech} and Viktor {Kocur} and Martin {Stuchlík} and Lukáš {Hudec} and Martin {Madaras}",
  title="Towards Deep Learning-based 6D Bin Pose Estimation in 3D Scans",
  booktitle="Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP",
  year="2022",
  pages="545--552",
  publisher="SciTePress - Science and Technology Publications",
  address="Setubal",
  doi="10.5220/0010878200003124",
  isbn="978-989-758-555-5",
  url="https://www.scitepress.org/Link.aspx?doi=10.5220/0010878200003124"
}