3D Registration in 30 Years: A Survey
Fuente:
arXiv
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866916532310769664 |
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| author | Yang, Jiaqi Zhang, Chu'ai Wang, Zhengbao Cao, Xinyue Ouyang, Xuan Zhang, Xiyu Zeng, Zhenxuan Zeng, Zhao Lu, Borui Xia, Zhiyi Zhang, Qian Guo, Yulan Zhang, Yanning |
| author_facet | Yang, Jiaqi Zhang, Chu'ai Wang, Zhengbao Cao, Xinyue Ouyang, Xuan Zhang, Xiyu Zeng, Zhenxuan Zeng, Zhao Lu, Borui Xia, Zhiyi Zhang, Qian Guo, Yulan Zhang, Yanning |
| contents | 3D point cloud registration is a fundamental problem in computer vision, computer graphics, robotics, remote sensing, and etc. Over the last thirty years, we have witnessed the amazing advancement in this area with numerous kinds of solutions. Although a handful of relevant surveys have been conducted, their coverage is still limited. In this work, we present a comprehensive survey on 3D point cloud registration, covering a set of sub-areas such as pairwise coarse registration, pairwise fine registration, multi-view registration, cross-scale registration, and multi-instance registration. The datasets, evaluation metrics, method taxonomy, discussions of the merits and demerits, insightful thoughts of future directions are comprehensively presented in this survey. The regularly updated project page of the survey is available at https://github.com/Amyyyy11/3D-Registration-in-30-Years-A-Survey. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_13735 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | 3D Registration in 30 Years: A Survey Yang, Jiaqi Zhang, Chu'ai Wang, Zhengbao Cao, Xinyue Ouyang, Xuan Zhang, Xiyu Zeng, Zhenxuan Zeng, Zhao Lu, Borui Xia, Zhiyi Zhang, Qian Guo, Yulan Zhang, Yanning Computer Vision and Pattern Recognition 3D point cloud registration is a fundamental problem in computer vision, computer graphics, robotics, remote sensing, and etc. Over the last thirty years, we have witnessed the amazing advancement in this area with numerous kinds of solutions. Although a handful of relevant surveys have been conducted, their coverage is still limited. In this work, we present a comprehensive survey on 3D point cloud registration, covering a set of sub-areas such as pairwise coarse registration, pairwise fine registration, multi-view registration, cross-scale registration, and multi-instance registration. The datasets, evaluation metrics, method taxonomy, discussions of the merits and demerits, insightful thoughts of future directions are comprehensively presented in this survey. The regularly updated project page of the survey is available at https://github.com/Amyyyy11/3D-Registration-in-30-Years-A-Survey. |
| title | 3D Registration in 30 Years: A Survey |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2412.13735 |