利用PCL处理Realsense点云数据-显示点云法线方向及出现问题的解决

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在我们获得点云数据后，为了能够进行表面重建或者是进行物体的位姿确定，我们都需要确定物体表面的发现方向。

PCL中有现成的计算物体法线的类NormalEstimation，这个类做了以下3件事

1.得到p的最近邻

2.计算p的表面法线n

3.检查法线的朝向，然后拨乱反正。

默认的视角是(0,0,0)

计算一个点的法线

computePointNormal (const pcl::PointCloud<PointInT> &cloud, const std::vector<int> &indices, Eigen::Vector4f &plane_parameters, float &curvature);

前面两个参数很好理解，plane_parameters包含了4个参数，前面三个是法线的(nx,ny,nz)坐标，加上一个 nc .p_plane (centroid here) + p的坐标，然后最后一个参数是曲率。

#include <iostream>#include <pcl/visualization/cloud_viewer.h>#include<pcl/io/pcd_io.h>#include<pcl/point_types.h>#include <pcl/conversions.h>#include <pcl/features/normal_3d.h>#include <boost/thread/thread.hpp>#include <pcl/common/common_headers.h>#include <pcl/filters/voxel_grid.h>#include <pcl/visualization/pcl_visualizer.h>#include <pcl/console/parse.h>#include <pcl/filters/statistical_outlier_removal.h>int main(){pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_old(new pcl::PointCloud<pcl::PointXYZ>);pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_downsampled(new pcl::PointCloud<pcl::PointXYZ>);pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);pcl::io::loadPCDFile("test_pcd.pcd", *cloud_old);//Use a voxelSampler to downsamplepcl::VoxelGrid<pcl::PointXYZ> voxelSampler;voxelSampler.setInputCloud(cloud_old);voxelSampler.setLeafSize(0.01f, 0.01f, 0.01f);voxelSampler.filter(*cloud_downsampled);//Use a filter to reduce noisepcl::StatisticalOutlierRemoval<pcl::PointXYZ> statFilter;statFilter.setInputCloud(cloud_downsampled);statFilter.setMeanK(10);statFilter.setStddevMulThresh(0.2);statFilter.filter(*cloud);// Create the normal estimation class, and pass the input dataset to itpcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> ne;ne.setInputCloud(cloud);// Create an empty kdtree representation, and pass it to the normal estimation object.// Its content will be filled inside the object, based on the given input dataset (as no other search surface is given).pcl::search::KdTree<pcl::PointXYZ>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZ>());ne.setSearchMethod(tree);// Output datasetspcl::PointCloud<pcl::Normal>::Ptr normals(new pcl::PointCloud<pcl::Normal>);// Use all neighbors in a sphere of radius 1cmne.setRadiusSearch(0.01);// Compute the featuresne.compute(*normals);boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));viewer->setBackgroundColor(0, 0, 0);viewer->addPointCloud<pcl::PointXYZ>(cloud, "sample cloud");viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 3, "sample cloud");viewer->addPointCloudNormals<pcl::PointXYZ, pcl::Normal>(cloud, normals, 10, 0.2, "normals");viewer->addCoordinateSystem(1.0);viewer->initCameraParameters();while (!viewer->wasStopped()){viewer->spinOnce(100);boost::this_thread::sleep(boost::posix_time::microseconds(100000));}return 0;}

但是第一次运行时出现了这样的问题，no ovverride found for vtkactor,解决这个问题其实很简单，首先加上#include <vtkAutoInit.h>

然后在mian的第一行加上VTK_MODULE_INIT(vtkRenderingOpenGL); 就没有问题了。

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