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Authors: Shuichi Akizuki and Manabu Hashimoto

Affiliation: Department of Engineering, Chukyo University, Nagoya, Aichi, Japan

Keyword(s): Dataset Generation, Semantic Segmentation, Affordance, 6DoF Pose Estimation.

Abstract: This paper introduces our ongoing work which is a project of establishing a novel dataset for the benchmarking of multiple robot vision tasks that aims to handle everyday objects. Our dataset is composed of 3D models, RGB-D input scenes and multi-type annotations. The 3D models are full-3D scan data of 100 everyday objects. Input scenes are over 54k RGB-D images that capture the table-top environment, including randomly placed everyday objects. Our dataset also provides four types of annotation: bounding boxes, affordance labels, object class labels, and 6 degrees of freedom (6DoF) poses. These are labeled for all objects in an image. These annotations are easily assigned to images via an original 6DoF annotation tool that has a simple graphical interface. We also report benchmarking results for modern object recognition algorithms.

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Paper citation in several formats:
Akizuki, S. and Hashimoto, M. (2020). A Multi-purpose RGB-D Dataset for Understanding Everyday Objects. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 470-475. DOI: 10.5220/0009142504700475

@conference{visapp20,
author={Shuichi Akizuki. and Manabu Hashimoto.},
title={A Multi-purpose RGB-D Dataset for Understanding Everyday Objects},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={470-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009142504700475},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - A Multi-purpose RGB-D Dataset for Understanding Everyday Objects
SN - 978-989-758-402-2
IS - 2184-4321
AU - Akizuki, S.
AU - Hashimoto, M.
PY - 2020
SP - 470
EP - 475
DO - 10.5220/0009142504700475
PB - SciTePress

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