搜索资源列表
shuju
- 书中使用主流的程序设计语言C++作为具体的实现语言。 书的内容包括表、栈、队列、树、散列表、优先队列、排序、不相交集算法、图论算法、算法分析 、算法设计、摊还分析、查找树算法、k-d树和配对堆等。 -Book using mainstream programming language C++ as a specific implementation language. The book includes tables, stacks, queues, trees, hash tables
kdtree1.2
- Kd-trees are data structures which are used to store points in k-dimensional space. As it follows its name, kd-tree is a tree. Tree leafs store points of the dataset (one or several points in each leaf). Each point is stored in one and only one leaf,
bkdtree
- opencv 成功案例，KD-Tree搜索临近点-OpenCV KD-tree matching
KD_tree
- 用于多节点创建的KD树创建，实现数据划分-KD tree is used to create a multi-node created, data division.
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”
kd_buildtree
- 以matlab2014a为实验平台实现KD树算法。可以参考。-protect KD tree in matlab 2014 a.
findPointNormals
- 基于kd-tree搜索算法，利用局部邻域的平面拟合，检测三维点云数据的法线方向- Estimates the normals of a sparse set of n 3d points by using a set of the closest neighbours to approximate a plane.
Kd_Tree
- 本段代码实现了kd-tree,提供了完整的k树代码-This code implements the kd-tree, the tree provides a complete k codes
findKN
- 在数据挖掘、人工智能等领域中，都常用到KD树来进行K近邻查找。本程序是自己用C++实现的一个KD树来进行的K近邻查找程序，包含建树和查找。文件中附有测试文件。-In data mining, artificial intelligence and other areas, it is commonly used to KD tree to find K nearest neighbor. This procedure is K neighbor Finder C++ they used to a
kdtree_search
- PCL官方文档中所带的kd树搜索的相关算法-PCL official documents related algorithms brought kd tree search
bbf
- 详细讲解BBF搜索遍历算法的原理以及与kd-tree的关联应用-In detail the BBF search times calendar calculation method and the principle of the associated application in kd- tree
knn-kdtree
- kd树，分割k维数据空间的数据结构。主要应用于多维空间关键数据的搜索（如：范围搜索和最近邻搜索）。K-D树是二进制空间分割树的特殊的情况。-KD tree, the data structure of K dimensional data space. It is mainly used in the search of key data in multidimensional space (such as range search and nearest neighbor search). K
python-algorithms-master
- python algrithms视频附例代码， 1. Log N Behavior 1.5 Big O SideBar 2. O(n log n) Behavior 3. Mathematical Algorithms 4. Brute Force Algorithms 5. KD Tree Data Structure 6. DepthFirstSearch 7. Seven All Pairs Shortest Path 8. Heap 9. Single-Source
KDTreeTest
- KD tree 实现算法，内有测试例子参考，可以学习里面的内容和思想。(KD tree algorithm.There is a test example of reference, and can learn the contents and ideas inside.)
kdTree-master
- C ++模板化的KD-Tree实现 这是KD-Tree空间数据结构的仅头部实现。 你只需要提供一个 具有已知编译时间“维度”字段的矢量类型和双重getDimension（size_t维度）方法。 目前支持以下操作： - 从点矢量创建 - 在一个点中心的立方体中查找点 - 从树中删除点（但不是从点的内部列表） - 采用任意函数参数的遍历方法 我已经成功地使用它来删除邻居太近的修剪一组点。(C++ templated KD-Tree implementation T
kdtree-master
- kd tree implementaion in scala spark
kdtree-scala-master
- Kd tree implementation in scala spark language
邻域计算
- kd树数据存储结构，进行klinyu搜索，GUI界面，具有保存搜索的k邻域数据(Kd tree data storage structure, k linyu search, GUI interface, with k neighborhood data to save the search)
create_kd_tree
- 通过计算方差，确定划分坐标轴，最后，将点云划分到一个个格子中，这样的好处在于可以将噪点和有效点分别存储于不同的格子中，方便进行去噪。(k-d tree create;By calculating the variance, the coordinate axis is determined. Finally, the point cloud is divided into a number of lattices. The advantage is that the noise and the