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Authors: Diego Rodriguez ; Florian Huber and Sven Behnke

Affiliation: Autonomous Intelligent Systems, University of Bonn, Bonn, Germany

Keyword(s): Non-rigid Registration, Robot Vision, Shape Spaces.

Abstract: In this paper, we propose a novel approach for registering objects in a non-rigid manner based on decomposed parts of an object category. By performing part-based registration, the deforming points match better local geometric structures of the observed instance. Moreover, the knowledge acquired of an object part can be transferred to different object categories that share the same decomposed part. This is possible because the registration is based on a learned latent space that encodes typical geometrical variations of each part independently. We evaluate our approach extensively on different object categories and demonstrate its robustness against outliers, noise and misalignments of the object pose.

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Paper citation in several formats:
Rodriguez, D., Huber, F. and Behnke, S. (2022). Category-level Part-based 3D Object Non-rigid Registration. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 795-802. DOI: 10.5220/0010761800003124

@conference{visapp22,
author={Diego Rodriguez and Florian Huber and Sven Behnke},
title={Category-level Part-based 3D Object Non-rigid Registration},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={795-802},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010761800003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Category-level Part-based 3D Object Non-rigid Registration
SN - 978-989-758-555-5
IS - 2184-4321
AU - Rodriguez, D.
AU - Huber, F.
AU - Behnke, S.
PY - 2022
SP - 795
EP - 802
DO - 10.5220/0010761800003124
PB - SciTePress

- Science and Technology Publications, Lda.
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