森林点云注册:一个审查
Jincheng Liu1, Yijun Guo1, Juntao Yang2
1College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China.
Forestry research
|November 11, 2024
概括
本综述系统地检查了超过20年的森林点云注册方法,从手动标记器到深度学习. 它涵盖了各种平台注册,数据集和指标,为推进森林调查技术提供了洞察力.
科学领域:
- 林业 林业 林业 林业 林业
- 地理学就是地质学.
- 计算机视觉 计算机视觉
背景情况:
- 精确的森林调查和管理依赖于准确的点云记录.
- 现有的审查缺乏对森林点云注册进展的全面,系统的概述.
研究的目的:
- 提供过去二十年来森林点云登记方法的系统审查.
- 分析不同平台 (地面,空中) 的注册情况,并讨论数据集和指标.
- 确定森林点云注册当前的挑战和未来的研究方向.
主要方法:
- 关于森林点云登记技术的文献综述.
- 基于发展阶段的方法分类:手动标记,特征匹配,深度学习.
- 分析地面-地面,地面-空中和空中-空中平台的注册情况.
主要成果:
- 记录了森林点云注册从手动到自动化和深度学习方法的演变.
- 讨论了从不同平台注册点云的复杂性和解决方案.
- 突出了关键数据集和评估指标,这些指标对于对比注册算法至关重要.
结论:
- 由于技术创新,森林点云注册取得了显著的进步.
- 需要进一步的研究来应对当前的挑战,并加强大规模森林管理中的应用.
- 本综述是该领域的研究人员和从业人员的基础资源.
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