Pose estimation for non-cooperative targets using 3D feature correspondences grouped via local and global constraints

Angfan Zhu, Jiaqi Yang, Zhiguo Cao, Li Wang, Yingying Gu

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

The pose of a non-cooperative target represented by point cloud can be estimated through point cloud registration, which is generally performed by searching good correspondences. Seeking correspondences in the context of non-cooperative target pose estimation is a challenging task due to the low texture, noise and occlusion, resulting in a number of outliers in the initial correspondences. In order to gain a high quality set of feature correspondences, we employ a combination of local and global constraints to remove the outliers in initial correspondences. On a local scale, we use simple and low-level geometric invariants. On a global scale, we apply covariant constraints for finding compatible correspondences. In the experiments, we use four groups of different non-cooperative targets to evaluate our algorithm and the results verify that the quality of the correspondence set has been greatly improved by our method and the pose can be accurately estimated.

源语言英语
主期刊名MIPPR 2019
主期刊副标题Pattern Recognition and Computer Vision
编辑Nong Sang, Jayaram K. Udupa, Yuehuan Wang, Zhenbing Liu
出版商SPIE
ISBN(电子版)9781510636378
DOI
出版状态已出版 - 2020
活动11th International Symposium on Multispectral Image Processing and Pattern Recognition: Pattern Recognition and Computer Vision, MIPPR 2019 - Wuhan, 中国
期限: 2 11月 20193 11月 2019

出版系列

姓名Proceedings of SPIE - The International Society for Optical Engineering
11430
ISSN(印刷版)0277-786X
ISSN(电子版)1996-756X

会议

会议11th International Symposium on Multispectral Image Processing and Pattern Recognition: Pattern Recognition and Computer Vision, MIPPR 2019
国家/地区中国
Wuhan
时期2/11/193/11/19

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