Skeleton features distribution for 3D object retrieval

Tomoki Hayashi, Benjamin Raynal, Vincent Nozick, Hideo Saito

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper, we propose a 3D shape similarity measurement method using the surface skeleton of a voxelized 3D shape. A set of features are extracted from the skeleton by combining the skeleton and the distance map of the subject. The distribution of these extracted features is used to represent the 3D shape. Two 3D shapes can be compared with a similarity score computed from the distance between their respective features distribution. Our method is robust to noise and to partial occlusion. Moreover, it is scale and rotation invariant. We tested and validated our method with various objects with different shape and topology.

本文言語English
ホスト出版物のタイトルProceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
ページ377-380
ページ数4
出版ステータスPublished - 2011 12 1
イベント12th IAPR Conference on Machine Vision Applications, MVA 2011 - Nara, Japan
継続期間: 2011 6 132011 6 15

出版物シリーズ

名前Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

Other

Other12th IAPR Conference on Machine Vision Applications, MVA 2011
CountryJapan
CityNara
Period11/6/1311/6/15

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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