# G3Reg **Repository Path**: nexusocc/G3Reg ## Basic Information - **Project Name**: G3Reg - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2024-08-14 - **Last Updated**: 2024-08-14 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README #
G3Reg:
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Pyramid Graph-based Global Registration using Gaussian Ellipsoid Model
Youtube PRs-Welcome stars FORK Issues
> [Zhijian Qiao](https://qiaozhijian.github.io/), Zehuan Yu, Binqian Jiang, [Huan Yin](https://huanyin94.github.io/), and [Shaojie Shen](https://uav.hkust.edu.hk/group/) > > IEEE Transactions on Automation Science and Engineering ### News * **`03 Apr 2024`:** Accepted by [IEEE TASE](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8856)! * **`19 Dec 2023`:** Conditionally Accept. * **`22 Aug 2023`:** We released our paper on Arxiv and submit it to [IEEE TASE](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8856). ## Abstract

G3Reg is a fast and robust global registration framework for point clouds.

**Features**: + **Fast matching**: We utilize segments, including planes, clusters, and lines, parameterized as Gaussian Ellipsoid Models (GEM) to facilitate registration. + **Robustness**: We introduce a distrust-and-verify scheme, termed Pyramid Compatibility Graph for Global Registration (PAGOR), designed to enhance the robustness of the registration process. + **Framework Integration**: Both GEM and PAGOR can be integrated into existing registration frameworks to boost their performance. **Note to Practitioners**: + **Application Scope**: The method outlined in this paper focuses on global registration of outdoor LiDAR point clouds. However, the fundamental principles of G3Reg, including segment-based matching and PAGOR, are applicable to any point-based registration tasks, including indoor environments. + **Segmentation Check**: If the registration does not perform as expected on your point cloud, it is advisable to review the segmentation results closely, referring to [Segmentation Demo](docs/demo.md). + **Alternative Matching Approaches**: For practitioners preferring not to use GEM-based matching, point-based matching is a viable alternative. For implementation details, please refer to the configuration file at [fpfh_pagor](configs/kitti_lc_bm/fpfh_pagor.yaml). + **Limitations**: Segment-based matching may be less effective in environments with sparse geometric information, such as areas with dense vegetation. In such scenarios, enhancing segment descriptions through hand-crafted or deep learning-based descriptors is recommended to improve matching accuracy. ## Getting Started - [Installation](docs/install.md) - [Demo](docs/demo.md) - [Benchmarks](docs/benchmarks.md) ## Qualitative results on datasets ### KITTI-08 https://github.com/HKUST-Aerial-Robotics/G3Reg/assets/21232185/8f4091b5-5305-4236-afb6-00ea5799ecd7 ### Apollo-Highway https://github.com/HKUST-Aerial-Robotics/G3Reg/assets/21232185/f1d4c9ad-04e9-4cf4-890a-12714f74eb59 ### Apollo-Sunnyvale https://github.com/HKUST-Aerial-Robotics/G3Reg/assets/21232185/60c7bf50-cd1c-447d-964d-1902e4db0489 ### Livox-HIT-1 https://github.com/HKUST-Aerial-Robotics/G3Reg/assets/21232185/ee1d9dd1-d460-4970-b060-ada25bc8e004 ### Livox-HIT-3 https://github.com/HKUST-Aerial-Robotics/G3Reg/assets/21232185/ef453f89-c92b-4d26-b232-3db2e3bac3f3 ## Application to Multi-session Map Merging
map_merging
## Acknowledgements We would like to show our greatest respect to authors of the following repos for making their works public: * [Teaser](https://github.com/MIT-SPARK/TEASER-plusplus) * [Segregator](https://github.com/Pamphlett/Segregator) * [Quatro](https://github.com/url-kaist/Quatro) * [3D-Registration-with-Maximal-Cliques](https://github.com/zhangxy0517/3D-Registration-with-Maximal-Cliques) ## Citation If you find G3Reg is useful in your research or applications, please consider giving us a star 🌟 and citing it by the following BibTeX entry. ```bibtex @ARTICLE{qiao2024g3reg, author={Qiao, Zhijian and Yu, Zehuan and Jiang, Binqian and Yin, Huan and Shen, Shaojie}, journal={IEEE Transactions on Automation Science and Engineering}, title={G3Reg: Pyramid Graph-Based Global Registration Using Gaussian Ellipsoid Model}, year={2024}, volume={}, number={}, pages={1-17}, keywords={Point cloud compression;Three-dimensional displays;Laser radar;Ellipsoids;Robustness;Upper bound;Uncertainty;Global registration;point cloud;LiDAR;graph theory;robust estimation}, doi={10.1109/TASE.2024.3394519}} ``` ```bibtex @inproceedings{qiao2023pyramid, title={Pyramid Semantic Graph-based Global Point Cloud Registration with Low Overlap}, author={Qiao, Zhijian and Yu, Zehuan and Yin, Huan and Shen, Shaojie}, booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages={11202--11209}, year={2023}, organization={IEEE} } ```