DPN-LRF: A local reference frame for robustly handling density differences and partial occlusions

Shuichi Akizuki, Manabu Hashimoto

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

For the purpose of 3D keypoint matching, a Local Reference Frame (LRF), a local coordinate system of the keypoint, is one important information source for achieving repeatable feature descriptions and accurate pose estimations. We propose a robust LRF for two main point cloud disturbances: density differences and partial occlusions. To generate LRFs that are robust to such disturbances, we employ two strategies: normalizing the effects of point cloud density by approximating the surface area in the local region and using the dominant orientation of a normal vector around the keypoint. Experiments confirm that the proposed method has higher repeatability than state-of-the-art methods with respect to density differences and partial occlusions. It was also confirmed that the method enhances the reliability of keypoint matching.

本文言語English
ホスト出版物のタイトルAdvances in Visual Computing - 11th International Symposium, ISVC 2015, Proceedings
出版社Springer Verlag
ページ878-887
ページ数10
9474
ISBN(印刷版)9783319278568
DOI
出版ステータスPublished - 2015
外部発表はい
イベント11th International Symposium on Advances in Visual Computing, ISVC 2015 - Las Vegas, United States
継続期間: 2015 12月 142015 12月 16

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9474
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other11th International Symposium on Advances in Visual Computing, ISVC 2015
国/地域United States
CityLas Vegas
Period15/12/1415/12/16

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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