AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Computational Visual Media Article
PDF (7 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

6DOF pose estimation of a 3D rigid object based on edge-enhanced point pair features

College of Computing, National University of Defense Technology, Changsha 410073, China
Department of Spine Surgery, the Second Xiangya Hospital, Central South University, Changsha 410011, China
Clinical Nursing Teaching and Research Section, the Second Xiangya Hospital, Changsha 410011, China
College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China
Beijing Institute of Tracking and Communication Technology, Beijing 100094, China
Show Author Information

Abstract

The point pair feature (PPF) is widely used for 6D pose estimation. In this paper, we propose an efficient 6D pose estimation method based on the PPF framework. We introduce a well-targeted down-sampling strategy that focuses on edge areas for efficient feature extraction for complex geometry. A pose hypothesis validation approach is proposed to resolve ambiguity due to symmetry by calculating the edge matching degree. We perform evaluations on two challenging datasets and one real-world collected dataset, demonstrating the superiority of our method for pose estimation for geometrically complex, occluded, symmetrical objects. We further validate our method by applying it to simulated punctures.

Graphical Abstract

Keywords

point pair feature (PPF)pose estimationobject recognition3D point cloud

References

【1】
【1】
 
 
Crossref Google Scholar
Computational Visual Media
Volume 10 Issue 1,
February 2024
Pages 61-77
DOI: 10.1007/s41095-022-0308-2

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Cite this Report
Close
Close
Cite this article:
Liu C, Chen F, Deng L, et al. 6DOF pose estimation of a 3D rigid object based on edge-enhanced point pair features. Computational Visual Media, 2024, 10(1): 61-77. https://doi.org/10.1007/s41095-022-0308-2

1453

Views

103

Downloads

9

Crossref

5

Web of Science

9

Scopus

1

CSCD
Received: 12 May 2022
Accepted: 16 August 2022
Published: 30 November 2023
© The Author(s) 2023.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduc-tion in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www.editorialmanager.com/cvmj.