PCL八叉树 getPointIndicesFromNewVoxels 点云比对-CSDN博客

本文链接：https://blog.csdn.net/zxcvb036/article/details/113772512

本文介绍如何使用PCL中的八叉树结构（OctreePointCloudChangeDetector）来检测两个点云（cloudA和B）之间的差异，重点在于找出B中不属于A的点。通过维护两个缓冲区并重用节点对象，减少了内存分配和释放操作，提高了效率。

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查找B点云中不属于A点云的点
Point cloud cloudA is our reference point cloud and the octree structure describe its spatial distribution. The class OctreePointCloudChangeDetector inherits from class Octree2BufBase which enables to keep and manage two octrees in the memory at the same time. In addition, it implements a memory pool that reuses already allocated node objects and therefore reduces expensive memory allocation and deallocation operations when generating octrees of multiple point clouds. By calling “octree.switchBuffers()”, we reset the octree class while keeping the previous octree structure in memory.

#include <pcl/point_cloud.h>
#include <pcl/octree/octree_pointcloud_changedetector.h>
#include<iostream>
#include<vector>
#include<ctime>
#include <pcl/visualization/pcl_visualizer.h>
 


int main(int argc, char** argv)
{
   


	//In order to retrieve points that are stored at voxels of the current octree structure (based on cloudB) which did not exist in the previous octree structure (based on cloudA),


	srand((unsigned int) time(NULL));

	float resolution = 32.0f;

	pcl::octree::OctreePointCloudChangeDetector < pcl::PointXYZ> octree(resolution);
	pcl::PointCloud < pcl::PointXYZ>::Ptr cloudA(new  pcl::PointCloud<pcl::PointXYZ>());


	cloudA->width = 128;
	cloudA->height = 1;
	cloudA->resize(cloudA-></