搜索资源列表
Quater_Registration
- 四元数分解的点云配准,输入点云的源坐标和目标坐标,计算期望的旋转矩阵和平移向量。-Quaternion decomposition point cloud registration, input the source and target point cloud coordinates to calculate the expected rotation matrix and translation vector.
sour
- 点云配准的ICP代码的输出 可以输出变换矩阵和变换向量-Output point cloud registration of ICP codes can be output transformation matrix and transformation vector
icp
- ICP算法实现点云配准,在pcl点云库课本第13章第二节实例的基础上进行了改进,实现了更精确配准-ICP algorithm for point cloud registration, in Chapter 13, Section instance pcl basis point cloud library textbook has been improved to achieve a more accurate registration
bunny2
- pcd点云文件格式,在pcl点云库中实现两个pcd文件的点云配准-pcd point cloud file formats to achieve two pcd file in the library pcl point cloud point cloud registration
CPD
- 点云配准算法CPD,可搜索相关论文,有matlab版,此为C++改编版,不完善,慎下。coherent pointcloud alignment
myICP
- 使用matlab实现的icp算法,用于两幅不同视角的深度图像点云配准。-icp algorithm(matlab version)
icp
- Matlab经典的ICP点云配准算法,内部包含三个例子,亲测可用。-Matlab classic ICP point cloud registration algorithm. There are three examples in the Zip file. I have texted that it can be used successfully.
jiguangsaomiao
- 有关于地面三维激光扫描的点云数据处理,模型构建和点云配准的各种文章-On the ground three-dimensional laser scanning point cloud data processing, model building and various articles of point cloud registration
registration
- point cloud 点云配准计算,通过选择几组匹配的点云数据对对点云数据进行配准处理-point cloud point cloud registration computing, by selecting a set of match point cloud data point cloud data registration process
icp
- 点云配准ICP算法,实现散乱点云的匹配,经典算法。基于MATLAB和VC实现,操作简单-point cloud ICP registration algorithm,classical algorithm of scattered point cloud matching . Based on MATLAB and VC implement, easy to operate.
PCLCode
- PCL课本全章源码的,包含I/O,kd-tree,八叉树,可视化,滤波,深度图像,关键点。采样一致性算法,点云特征描述与提取,点云配准,点云分割,点云曲面重建-the code of book“Point Cloud Library”
icp.m
- 三维点云配准,icp原代码,亲测有效,适合初学者学习。-3D point cloud registration, icp source code, effective pro-test, suitable for beginners to learn.
4ysfcpp
- 四元数法点云配准 点坐标保存在excel中,用matlab读入-point cloud register
ICP-point-cloud-registration
- 三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低,提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准,获得较好 的点云初始位置,然后在经典 ICP 算法的基础上,采用 k - d tree 结构实现加速搜索,并利用方向向量夹角阈值去除 错误点对,提高算法的效率。实验表明,本算法流程在保证配准精度的前提下,显著提高了配准效率。 -Three-dimensional laser point cl
laser-kinect-pointcloud-register-icp
- 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。
kd-tree.cpp
- 三维点云配准kd-tree搜索算法,用于特征点的搜索匹配-3 d point cloud registration kd- tree search algorithm, is used to search of feature point matching
test_peizhun
- 基于PCL的点云配准处理主程序,基于点云库实现,可以进行点云的拼接-PCL-based point cloud registration processing main program, based on point cloud library implementation, you can point cloud of the stitching
pairwise_incremental_registration
- 用ICP进行点云的两两配准,点云配准,C++(ICP with two points of the cloud registration)
normal_distributions_transform
- 此代码采用正态分布变换算法NDT进行点云配准(This code uses the normal distribution transform algorithm NDT for point cloud registration)
qt_ndt
- 调用PCL的DNT算法进行点云配准,需要pcl调用库(Call PCL DNT algorithm for point cloud registration, you need PCL call library)