6D0F pose estimation for similar objects using spatial relationship of part-affordance

Shuichi Akizuki, Yoshimitsu Aoki

研究成果: Article

抄録

In this paper, we propose a method to estimate 6D pose (3D position and pose) of the everyday objects, especially Kitchen or DIY tools, even if there are not the same 3D model of the target object. We assume that the tools that belong to same category have common spatial relation in part-affordances, the role of each part. The proposed method uses this assumption for pose estimation. By minimizing two types of consistencies, the spatial relationship of part-affordances and the shapes, we have confirmed that the proposed method achieved higher performance compared with traditional pose estimation method.

元の言語English
ページ(範囲)107-112
ページ数6
ジャーナルSeimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering
85
発行部数1
DOI
出版物ステータスPublished - 2019 1 1

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Kitchens

ASJC Scopus subject areas

  • Mechanical Engineering

これを引用

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abstract = "In this paper, we propose a method to estimate 6D pose (3D position and pose) of the everyday objects, especially Kitchen or DIY tools, even if there are not the same 3D model of the target object. We assume that the tools that belong to same category have common spatial relation in part-affordances, the role of each part. The proposed method uses this assumption for pose estimation. By minimizing two types of consistencies, the spatial relationship of part-affordances and the shapes, we have confirmed that the proposed method achieved higher performance compared with traditional pose estimation method.",
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AB - In this paper, we propose a method to estimate 6D pose (3D position and pose) of the everyday objects, especially Kitchen or DIY tools, even if there are not the same 3D model of the target object. We assume that the tools that belong to same category have common spatial relation in part-affordances, the role of each part. The proposed method uses this assumption for pose estimation. By minimizing two types of consistencies, the spatial relationship of part-affordances and the shapes, we have confirmed that the proposed method achieved higher performance compared with traditional pose estimation method.

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KW - Affordance

KW - Point cloud processing

KW - Pose estimation

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