PCL笔记三：点云连接；点云简单拼接

点云数据拼接与信息融合

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本文介绍了如何使用PCL库进行两种点云数据的拼接：同类型点云直接拼接和xyz点云与法线信息的融合。在直接拼接中，需要注意去重、排异和对齐等操作。在融合过程中，利用pcl::concatenateFields将点云的xyz坐标与法线信息结合成新的PointNormal类型点云。

连接两个不同的点云为一个点云。两种情况：

同种类型点云拼接：
同样N个点的xyz和rgb拼接：或者xyz与Normal的拼接。

注意不同点云类型的转换。

第一种：同种类型点云直接拼接。

#include<iostream>
#include<pcl/io/pcd_io.h>
#include<pcl/point_types.h>
using namespace std;



int main()
{
	pcl::PointCloud<pcl::PointXYZ>cloud_a, cloud_b, cloud_c;

	cerr << "Cloud A:" << endl;
	cloud_a.width = 5;
	cloud_a.height = cloud_b.height = 1;
	cloud_a.points.resize(cloud_a.width * cloud_a.height);
	for (size_t i = 0; i < cloud_a.size(); i++)
	{
		cloud_a.points[i].x = 1024 * rand() / (RAND_MAX + 1.0f);
		cloud_a.points[i].y = 1024 * rand() / (RAND_MAX + 1.0f);
		cloud_a.points[i].z = 1024 * rand() / (RAND_MAX + 1.0f);
		cerr << " " << cloud_a.points[i].x << " " << cloud_a.points[i].y << " " << cloud_a.points[i].z << endl;
	}

	cerr << "Cloud B:" << endl;
	cloud_b.width = 3;
	cloud_b.points.resize(cloud_b.width * cloud_b.height);

	for (size_t i = 0; i < cloud_b.size(); i++)
	{
		cloud_b.points[i].x = 1024 * rand() / (RAND_MAX + 1.0f);
		cloud_b.points[i].y = 1024 * rand() / (RAND_MAX + 1.0f);
		cloud_b.points[i].z = 1024 * rand() / (RAND_MAX + 1.0f);
		cerr << " " << cloud_b.points[i].x << " " << cloud_b.points[i].y << " " << cloud_b.points[i].z << endl;
	}

    cout << endl;
	cerr << "拼接之后：Cloud C:" << endl;
	cloud_c = cloud_a;
	cloud_c += cloud_b;   // 简单粗暴。
	for (size_t i = 0; i < cloud_c.size(); i++)
	{
		cerr << " " << cloud_c.points[i].x << " " << cloud_c.points[i].y << " " << cloud_c.points[i].z << endl;
	}
}

输出：

Cloud A:
 1.28125 577.094 197.938
 828.125 599.031 491.375
 358.688 917.438 842.563
 764.5 178.281 879.531
 727.531 525.844 311.281
Cloud B:
 15.3438 93.5938 373.188
 150.844 169.875 1012.22
 456.375 121.938 4.78125

拼接之后：Cloud C:
 1.28125 577.094 197.938
 828.125 599.031 491.375
 358.688 917.438 842.563
 764.5 178.281 879.531
 727.531 525.844 311.281
 15.3438 93.5938 373.188
 150.844 169.875 1012.22
 456.375 121.938 4.78125

缺少去重，排异，对齐等操作。

第二种：同样N个点的xyz和rgb拼接：或者xyz与Normal的拼接。

#include<iostream>
#include<pcl/io/pcd_io.h>
#include<pcl/point_types.h>
using namespace std;


int main()
{
	pcl::PointCloud<pcl::PointXYZ>cloud_a;
	pcl::PointCloud<pcl::Normal>n_cloud_b;
	pcl::PointCloud<pcl::PointNormal> p_n_cloud_c;

	cerr << "Cloud A:" << endl;
	cloud_a.width = 5;
	cloud_a.height = n_cloud_b.height = 1;
	cloud_a.points.resize(cloud_a.width * cloud_a.height);
	for (size_t i = 0; i < cloud_a.size(); i++)
	{
		cloud_a.points[i].x = 1024 * rand() / (RAND_MAX + 1.0f);
		cloud_a.points[i].y = 1024 * rand() / (RAND_MAX + 1.0f);
		cloud_a.points[i].z = 1024 * rand() / (RAND_MAX + 1.0f);
		cerr << " " << cloud_a.points[i].x << " " << cloud_a.points[i].y << " " << cloud_a.points[i].z << endl;
	}

	cerr << "Cloud B:" << endl;
	n_cloud_b.width = 5;
	n_cloud_b.points.resize(n_cloud_b.width * n_cloud_b.height);
	for (size_t i = 0; i < n_cloud_b.size(); i++)
	{
		n_cloud_b.points[i].normal[0] = 1024 * rand() / (RAND_MAX + 1.0f);
		n_cloud_b.points[i].normal[1] = 1024 * rand() / (RAND_MAX + 1.0f);
		n_cloud_b.points[i].normal[2] = 1024 * rand() / (RAND_MAX + 1.0f);
		cout << " " << n_cloud_b.points[i].normal[0] << " " << n_cloud_b.points[i].normal[1] << n_cloud_b.points[i].normal[2] << endl;
	}

	cout << endl;
	cout << "Cloud C:" << endl;
	pcl::concatenateFields(cloud_a, n_cloud_b, p_n_cloud_c);
	for (size_t i = 0; i < p_n_cloud_c.size(); i++)
	{
		cerr << " " << p_n_cloud_c.points[i].x << " " << p_n_cloud_c.points[i].y << " " << p_n_cloud_c.points[i].z
			<< " " << p_n_cloud_c.points[i].normal[0] << " " << p_n_cloud_c.points[i].normal[1]
			<< " " << p_n_cloud_c.points[i].normal[2] << endl;
	}
}

cloud_b可以看作法线或者RGB等信息。

Cloud A:
 1.28125 577.094 197.938
 828.125 599.031 491.375
 358.688 917.438 842.563
 764.5 178.281 879.531
 727.531 525.844 311.281
Cloud B:
 15.3438 93.5938373.188
 150.844 169.8751012.22
 456.375 121.9384.78125
 9.125 386.938544.406
 584.875 616.188621.719

Cloud C:
 1.28125 577.094 197.938 15.3438 93.5938 373.188
 828.125 599.031 491.375 150.844 169.875 1012.22
 358.688 917.438 842.563 456.375 121.938 4.78125
 764.5 178.281 879.531 9.125 386.938 544.406
 727.531 525.844 311.281 584.875 616.188 621.719