A large-scale multiview point cloud registration method based on distance statistical distribution of weak features
-д хадгалсан:
| -д хэвлэсэн: | Journal of Computational Design and Engineering vol. 12, no. 1 (Jan 2025), p. 312 |
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| Үндсэн зохиолч: | |
| Бусад зохиолчид: | , , , , |
| Хэвлэсэн: |
Oxford University Press
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| Нөхцлүүд: | |
| Онлайн хандалт: | Citation/Abstract Full Text - PDF |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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MARC
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|---|---|---|---|
| 001 | 3204104755 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2288-5048 | ||
| 024 | 7 | |a 10.1093/jcde/qwaf001 |2 doi | |
| 035 | |a 3204104755 | ||
| 045 | 2 | |b d20250101 |b d20250131 | |
| 100 | 1 | |a Feng, Yun |u School of Mechanical Science and Engineering, HuaZhong University of Science and Technology , Wuhan 430000 , Hubei, China | |
| 245 | 1 | |a A large-scale multiview point cloud registration method based on distance statistical distribution of weak features | |
| 260 | |b Oxford University Press |c Jan 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a There are issues such as poor layered smoothness, model distortion, and error accumulation in the process of large-scale weak feature point cloud stitching and registration. This paper proposes a precise point cloud registration method based on distance statistical distribution. By summarizing and statistically analyzing the distance thresholds during the iterative process, it accurately determines the closest points for point cloud registration, thus avoiding the problem of low registration accuracy caused by manually setting distance thresholds. By statistically analyzing the distance intervals of corresponding points in the point cloud to eliminate erroneous correspondences and utilizing pose graph optimization for global pose, this method ensures the smoothness and accuracy of point cloud registration. Experiments have validated the effectiveness of this method. Comparative experiments have demonstrated that this method surpasses traditional point cloud registration methods in terms of accuracy, convergence, and robustness. | |
| 653 | |a Stitching | ||
| 653 | |a Thresholds | ||
| 653 | |a Smoothness | ||
| 653 | |a Image registration | ||
| 653 | |a Engineering | ||
| 653 | |a Methods | ||
| 653 | |a Registration | ||
| 653 | |a Algorithms | ||
| 653 | |a Probability distribution | ||
| 653 | |a Optimization | ||
| 653 | |a Efficiency | ||
| 700 | 1 | |a Tao, Guoren |u Guilin Measuring & Cutting Tool Co., Ltd , Guilin 541000 , Guangxi, China | |
| 700 | 1 | |a Wu, Wenlei |u Guilin Measuring & Cutting Tool Co., Ltd , Guilin 541000 , Guangxi, China | |
| 700 | 1 | |a Lin, Jiahao |u Guilin Measuring & Cutting Tool Co., Ltd , Guilin 541000 , Guangxi, China | |
| 700 | 1 | |a Liu, Xiaojun |u School of Mechanical Science and Engineering, HuaZhong University of Science and Technology , Wuhan 430000 , Hubei, China | |
| 700 | 1 | |a Chen, Liangzhou |u School of Mechanical Science and Engineering, HuaZhong University of Science and Technology , Wuhan 430000 , Hubei, China | |
| 773 | 0 | |t Journal of Computational Design and Engineering |g vol. 12, no. 1 (Jan 2025), p. 312 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3204104755/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3204104755/fulltextPDF/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |