Description: Iterative Closest points算法，被广泛应用在3d领域，这里实现了将两团点云align到一起的功能-Iterative Closest points algorithm, has been widely used in the field of 3d, where the implementation of the two groups to align with the point cloud of the function Platform: |
Size: 23552 |
Author:xi |
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Description: matlab完美实现ICP（迭代最近点算法）算法，功能强大，适合匹配数据点-matlab perfect realization of ICP (iterative closest point algorithm) algorithm, a powerful, data points for matching Platform: |
Size: 60416 |
Author:xiaoxiaoming |
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Description: 迭代最近点算法，用于匹配数据点集。matlab实现-Iterative closest point algorithm is used to match the data points. matlab implementation Platform: |
Size: 5120 |
Author:李伟 |
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Description: 迭代最近点算法的一个简单实现，并使用了两个二维点集进行测试-an implementation and validation for the data association of two 2d point sets based on iterative closest points Platform: |
Size: 4096 |
Author:yangyuanzhe |
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Description: 针对三维重建中的点云配准问题，提出一种基于点云特征的自动配准算法。利用微软Kinect传感器采集物
体的多视角深度图像，提取目标区域并转化为三维点云。对点云进行滤波并估计快速点特征直方图特征，结合双向
快速近似最近邻搜索算法得到初始对应点集，并使用随机采样一致性算法确定最终对应点集。根据奇异值分解法
求出点云的变换矩阵初始值，在初始配准的基础上运用迭代最近点算法做精细配准。实验结果表明，该配准方法既
保证了三维点云的配准质量，又降低了计算复杂度，具有较高的可操作性和鲁棒性。
-Aiming at the problem of point cloud registration in 3D reconstruction, this paper presents an automatic regis-
tration method based on the feature of point cloud. Firstly, it utilizes Microsoft Kinect sensor to capture depth images in
several different views and the interest regions are extracted and converted to 3D point cloud. Secondly, point clouds are
filtered and the fast point feature histograms are estimated, then the bidirectional fast approximate nearest neighbor algorithm
and random sample consensus are employed to search the final corresponding points. Finally, after computing the initial
transformation matric applying singular value decomposition, the iterative closest point algorithm is used to get refined
result on the base of initial registration. Experiments show that this registration method can not only ensure the quality of
point cloud registration, but reduce the computation complexity, and achieve higher maneuverability and better robustness.
Platform: |
Size: 4065280 |
Author:zhaotianyang |
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Search - iterative closest points