pcl之kdtree的使用
阿新 • • 發佈:2018-11-09
pcl之kdtree的使用
A k-d tree, or k-dimensional tree, is a data structure used in computer science for organizing some number of points in a space with k dimensions. It is a binary search tree with other constraints imposed on it. K-d trees are very useful for range and nearest neighbor searches.
#include <pcl/point_cloud.h> #include <pcl/kdtree/kdtree_flann.h> #include <iostream> #include <vector> int main(int argc, char** argv) { pcl::PointCloud<pcl::PointXYZI>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZI>); .... pcl::KdTreeFLANN<pcl::PointXYZI> kdtree; kdtree.setIputCloud(cloud); pcl::PointXYZI search_point; .... // k nearest neighbor search int k = 10; std::vector<int> k_indices(k); std::vector<float> k_sqr_distances(k;) if (kdtree.nearestKSearch(search_point, k, k_indices, k_sqr_distances) > 0) { //do something } // neighbors within radius search float radius = 1.0; std::vector<int> std::vector<float> if (kdtree.radiusSearch(search_point, radius, radius_indices, radius_sqr_distance) > 0) { //do something } }
值得注意的是: 返回的是square_distance
參考
http://pointclouds.org/documentation/tutorials/kdtree_search.php