Alignment of 3D shape data by hashing sets of feature points

Yuka Kohno*, Osamu Yamaguchi, Toshio Sato, Bunpei Irie

*この研究の対応する著者

研究成果: Conference contribution

抄録

This paper presents a method to automatically align a pose of 3D shape data to fit another shape data taken from different viewpoints. One of the difficult issues is to handle shape data which have surface information in different sides due to the difference in viewpoints, and to deal with objects in different scale. We detect local feature points on the two shape data, make potentially corresponding pairs of three feature points, calculate transformation parameters to align the three points, and get optimal alignment parameters by the voting of parameters obtained from the pairs of three points. We used hash table to avoid combinatorial explosion in making the pairs, and used geometric invariants for its key which are calculated from the positions of the points to keep the scale invariance. The method was evaluated with some public data and a set of laser-scanned data, and proved to be effective in alignment of shape data in different angles or scales.

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120-123
ページ数4
出版ステータスPublished - 2011
外部発表はい
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

Conference

Conference12th IAPR Conference on Machine Vision Applications, MVA 2011
国/地域Japan
CityNara
Period11/6/1311/6/15

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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