Integration of Multiple RGB-D Data of a Deformed Clothing Item into Its Canonical Shape

Yasuyo Kita, Ichiro Matsuda, Nobuyuki Kita

2021

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.

Paper Citation

in Harvard Style

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, SciTePress, pages 910-918. DOI: 10.5220/0010228209100918

in Bibtex Style

@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},
}

in EndNote Style

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
AU - Kita Y.
AU - Matsuda I.
AU - Kita N.
PY - 2021
SP - 910
EP - 918
DO - 10.5220/0010228209100918
PB - SciTePress