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基于几何约束和转换评估的点云注册方法
Chuanli Kang1,2, Chongming Geng1, Zitao Lin1
1College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China.
Sensors (Basel, Switzerland)
|March 28, 2024
概括
这项研究引入了对点云的新型粗略注册方法,通过使用几何约束和矩阵评估来显著提高准确性和效率,并且对应数更少. 该方法通过减少来自不正确匹配和噪音数据的错误来增强点云注册.
科学领域:
- 计算机视觉 计算机视觉
- 几何计算几何计算
- 3D数据处理 3D数据处理
背景情况:
- 现有的点对点注册方法由于错误匹配和杂的对应而面临准确性和效率的挑战.
- 传统方法通常需要至少三个对应,限制了它们的适用性和速度.
研究的目的:
- 为点云开发一种新的粗略注册方法,克服现有技术的局限性.
- 通过使用几何约束和矩阵评估来提高注册准确性和效率.
主要方法:
- 一种使用几何约束和矩阵评估的新型粗略注册方法.
- 使用描述符和关键点检测的组合生成的初始对应.
- 使用近邻相似率 (NNSR) 选择高质量的对应物,并使用刚性和突出点的距离约束来评估.
- 转换矩阵仅使用两个对应函数进行计算,为最佳对齐推断逆转换.
- 基于重叠比率和inlier点的评估,以确定最好的转换点云.
主要成果:
- 与传统方法相比,拟议的方法实现了更高的准确性和效率,通过较低的根平均平方误差 (RMSE) 值来证明这一点.
- 选择生成初始对应的组合在注册准确性方面优于其他组合.
- 对比实验证实了该方法的卓越准确性,与各种点云数据集中的几个特征匹配注册技术相比.
结论:
- 拟议的基于几何约束和矩阵评估的粗略注册方法显著提高了点云注册的准确性和效率.
- 该方法需要更少的代,并在各种点云数据集上表现出强大的性能.
- 这种方法为点云注册挑战提供了更可靠的解决方案.
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