我创建了一个自定义的双点类型,用于将点位置存储在PCD文件中。我需要双精度数据类型,因为我的点位于全局坐标中,并且具有非常大的值(从10 ^ 6到10 ^ 7的阶数),并且需要良好的精度。由于值很大,并且默认的FLOAT32精度受到限制,因此存在相当大的数据近似值,在可视化期间也可以看到。
我通过使用我拥有的数据包中来自GPS的初始全局参考坐标转换原始点云来创建此PCD。我使用的是15点精度。
我创建了一个单独的脚本来可视化此自定义点型PCD。但是通过视觉比较,我看不到FLOAT32和双数据类型PCD之间有任何显着差异。
Transformed_float_pcd_visualization
Transformed_double_pcd_visualization
您可以看到,transformd_double和transformd_float PCD非常相似且近似。与这两个相比,raw_float PCD相当不错。
我将附加PCD文件以供参考:
[我认为我在加载点云时跳过了一些事情,还需要做一些其他更改才能以双点精度显示点。
我使用了pcl_tools的“ pcl_viewer”来可视化FLOAT类型的PCD。
可视化自定义双点结构PCD的代码:
#define PCL_NO_PRECOMPILE
#include <iostream>
// #include "double_viz/pcl_double.h"
#include <pcl-1.7/pcl/common/common.h>
#include <pcl-1.7/pcl/io/pcd_io.h>
#include <pcl-1.7/pcl/visualization/pcl_visualizer.h>
#include <pcl-1.7/pcl/console/parse.h>
#include <pcl-1.7/pcl/point_cloud.h>
#include <pcl-1.7/pcl/point_types.h>
namespace pcl
{
#define PCL_ADD_UNION_POINT4D_DOUBLE \
union EIGEN_ALIGN16 { \
double data[4]; \
struct { \
double x; \
double y; \
double z; \
}; \
};
struct _PointXYZDouble
{
PCL_ADD_UNION_POINT4D_DOUBLE; // This adds the members x,y,z which can also be accessed using the point (which is float[4])
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
};
struct EIGEN_ALIGN16 PointXYZDouble : public _PointXYZDouble
{
inline PointXYZDouble (const _PointXYZDouble &p)
{
x = p.x; y = p.y; z = p.z; data[3] = 1.0;
}
inline PointXYZDouble ()
{
x = y = z = 0.0;
data[3] = 1.0;
}
inline PointXYZDouble (double _x, double _y, double _z)
{
x = _x; y = _y; z = _z;
data[3] = 1.0;
}
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
};
}
POINT_CLOUD_REGISTER_POINT_STRUCT (pcl::_PointXYZDouble,
(double, x, x)
(double, y, y)
(double, z, z)
)
POINT_CLOUD_REGISTER_POINT_WRAPPER(pcl::PointXYZDouble, pcl::_PointXYZDouble)
// This function displays the help
void
showHelp(char * program_name)
{
std::cout << std::endl;
std::cout << "Usage: " << program_name << " cloud_filename.[pcd]" << std::endl;
std::cout << "-h: Show this help." << std::endl;
}
// This is the main function
int
main (int argc, char** argv)
{
// Show help
if (pcl::console::find_switch (argc, argv, "-h") || pcl::console::find_switch (argc, argv, "--help"))
{
showHelp (argv[0]);
return 0;
}
// Fetch point cloud filename in arguments | Works with PCD
std::vector<int> filenames;
if (filenames.size () != 1)
{
filenames = pcl::console::parse_file_extension_argument (argc, argv, ".pcd");
if (filenames.size () != 1)
{
showHelp (argv[0]);
return -1;
}
}
// Load file | Works with PCD and PLY files
pcl::PointCloud<pcl::PointXYZDouble>::Ptr source_cloud (new pcl::PointCloud<pcl::PointXYZDouble> ());
if (pcl::io::loadPCDFile (argv[filenames[0]], *source_cloud) < 0)
{
std::cout << "Error loading point cloud " << argv[filenames[0]] << std::endl << std::endl;
showHelp (argv[0]);
return -1;
}
// Visualization
// printf( "\nPoint cloud colors : white = original point cloud\n"
// " red = transformed point cloud\n");
pcl::visualization::PCLVisualizer viewer ("Visualize double PCL");
// Define R,G,B colors for the point cloud
pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZDouble> source_cloud_color_handler (source_cloud, 100, 100, 100);
// We add the point cloud to the viewer and pass the color handler
viewer.addPointCloud (source_cloud, source_cloud_color_handler, "original_cloud");
viewer.addCoordinateSystem (1.0, "cloud", 0);
viewer.setBackgroundColor(0.05, 0.05, 0.05, 0); // Setting background to a dark grey
viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_OPACITY, 1, "original_cloud");
viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "original_cloud");
viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_LINE_WIDTH, 1, "original_cloud");
//viewer.setPosition(800, 400); // Setting visualiser window position
while (!viewer.wasStopped ()) // Display the visualiser until 'q' key is pressed
{
viewer.spinOnce ();
}
return 0;
}
我创建了一个自定义的双点类型,用于将点位置存储在PCD文件中。我需要双精度数据类型,因为我的点位于全局坐标中,并且具有非常大的值(顺序...
在raw_float文件中,大小字段已定义为每个4个字节:SIZE 4 4 4 4
,读取为两倍应为SIZE 8 8 8 8
。