1) iterative closest point
迭代最近点
1.
On the basis of this,a pole-map based localization was introduced which does map-matching using iterative closest points and can enhance the accuracy of localization.
在此基础上,采用基于柱图的定位方法,使用迭代最近点算法进行地图匹配,提高了定位精度。
2) ICP
最近点迭代
1.
Examples show that RMGA can achieve a better result and then the iterative closest point(ICP) algorithm can obtain a accurate registration.
针对不同视角下测量的点云在配准时计算量大、速度慢的缺点,提出了一种基于实数编码的多种群遗传算法的配准方法,可以克服标准遗传算法速度慢、精度差的缺点,有效地提高全局搜索能力,实验结果表明:实数编码的多种群遗传算法能够快速获得较好的配准结果,以此结果作为初始位置进行最近点迭代法配准,能迅速达到所要求的精度,获得理想的配准效果。
2.
An ICP and GPC based 3D planar scene integration algorithm is proposed in the software module.
介绍了系统的软件模块,提出了结合最近点迭代(ICP)和通用多边形裁剪(GPC)的3D平面场景合成方法。
3) ICP algorithm
迭代最近点算法
1.
In this paper, the reliability of the algorithm of terrain matching based on ICP algorithm was analyzed.
根据迭代最近点算法的原理,从几何直观的角度研究了地形辅助导航系统匹配的可靠性,推导了旋转和平移的可靠性公式,并进行了数字仿真,结果表明,本文推导的可靠性结论是正确的。
2.
As the traditional ICP algorithm is liable to get local minimization problem and have a bad performance of real-time,a BP neural network was presented in the ICP algorithm.
鉴于传统的迭代最近点算法存在着易陷入局部最优的缺陷和实时性不好的问题,提出了一种将BP神经网络引入迭代最近点算法中进行地形匹配的新方法。
4) iterative closet point algorithm
最近点迭代法
5) iterative liner closest point
迭代线性最近点
6) iterative closet point
最临近点迭代
1.
<Abstrcat>In contrast to the traditional method of comparison between the measurement pointcloud and complex surface,An idea of using CAD model directive ICP(iterative closet point) algorithm to register pointcloud and surface was proposed.
针对测量点云与CAD模型配准过程中普遍采用基于点云与曲面的匹配方法,提出了以CAD模型引导的最临近点迭代ICP(iterativeclosetpoint)配准方法,由CAD模型将复杂曲面离散生成引导目标点云,并采用四元数法求解引导目标点云与测量点云配准的旋转和平移矩阵。
补充资料：层层迭迭
1.见"层层迭迭"。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条