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Authors: Yasuyo Kita 1 ; Ichiro Matsuda 1 and Nobuyuki Kita 2

Affiliations: 1 Dept. Electrical Engineering, Faculty of Science and Technology, Tokyo University of Science, Noda, Japan ; 2 TICO-AIST Cooperative Research Laboratory for Advanced Logistics, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

Keyword(s): Recognition of Deformable Objects, Robot Vision, Automatic Handling of Clothing.

Abstract: To recognize a clothing item so that it can be handled automatically, we propose a method that integrates multiple partial views of the item into its canonical shape, that is, the shape when it is flattened on a planar table. When a clothing item is held by a robot hand, only part of the deformed item can be seen from one observation, which makes the recognition of the item very difficult. To remove the effect of deformation, we first virtually flatten the deformed clothing surface based on the geodesic distances between surface points, which equal their two-dimensional distances when the surface is flattened on a plane. The integration of multiple views is performed on this flattened image plane by aligning flattened views obtained from different observations. Appropriate view directions for efficient integration are also automatically determined. The experimental results using both synthetic and real data are demonstrated.

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Paper citation in several formats:
Kita, Y.; Matsuda, I. and Kita, N. (2021). Integration of Multiple RGB-D Data of a Deformed Clothing Item into Its Canonical Shape. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 910-918. DOI: 10.5220/0010228209100918

@conference{visapp21,
author={Yasuyo Kita. and Ichiro Matsuda. and Nobuyuki Kita.},
title={Integration of Multiple RGB-D Data of a Deformed Clothing Item into Its Canonical Shape},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={910-918},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010228209100918},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - Integration of Multiple RGB-D Data of a Deformed Clothing Item into Its Canonical Shape
SN - 978-989-758-488-6
IS - 2184-4321
AU - Kita, Y.
AU - Matsuda, I.
AU - Kita, N.
PY - 2021
SP - 910
EP - 918
DO - 10.5220/0010228209100918
PB - SciTePress

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