pcl 版本 代码语法问题

问题1

《点云库PCL从入门到精通》第五章  2 range_image_visualization 可视化深度图像例程时

编译器报错"camera_":不是"pcl::visualization::PCLVisualizer"的成员，报错代码如下：

    viewer.camera_.pos[0] = pos_vector[0];
    viewer.camera_.pos[1] = pos_vector[1];
    viewer.camera_.pos[2] = pos_vector[2];
    viewer.camera_.focal[0] = look_at_vector[0];
    viewer.camera_.focal[1] = look_at_vector[1];
    viewer.camera_.focal[2] = look_at_vector[2];
    viewer.camera_.view[0] = up_vector[0];
    viewer.camera_.view[1] = up_vector[1];
    viewer.camera_.view[2] = up_vector[2];

解决：PCL1.8的viewer已经没有camera_了，应使用函数setCameraPosition()替换。修改后的代码如下：

    viewer.setCameraPosition(pos_vector[0], pos_vector[1], pos_vector[2], look_at_vector[0],
        look_at_vector[1], look_at_vector[2], up_vector[0], up_vector[1], up_vector[2]);

 

 

 

boost::shared_ptr是可以共享所有权的指针，如果有多个这样的指针都指向同一个对象时，只有所有的指针都不指向该对象时，对象才会被销毁。

 

 

 

生成深度图的代码，目前有很多不懂得地方，需要下一步弄懂

#include <iostream>
#include <boost/thread/thread.hpp>
#include <pcl/common/common_headers.h>
#include <pcl/common/common_headers.h>
#include <pcl/range_image/range_image.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/range_image_visualizer.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/console/parse.h>

typedef pcl::PointXYZ PointType;
// 全局参数
float angular_resolution = 0.5f;
pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;
bool live_update = false;
// -----打印帮助-----
void
printUsage(const char* progName)
{
    std::cout << "\n\nUsage: " << progName << " [options] <scene.pcd>\n\n"
        << "Options:\n"
        << "-------------------------------------------\n"
        << "-r <float>   angular resolution in degrees (default " << angular_resolution << ")\n"
        << "-c <int>     coordinate frame (default " << (int)coordinate_frame << ")\n"
        << "-l           live update - update the range image according to the selected view in the 3D viewer.\n"
        << "-h           this help\n"
        << "\n\n";
}

void
setViewerPose(pcl::visualization::PCLVisualizer& viewer, const Eigen::Affine3f& viewer_pose)
{
    Eigen::Vector3f pos_vector = viewer_pose * Eigen::Vector3f(0, 0, 0);
    Eigen::Vector3f look_at_vector = viewer_pose.rotation() * Eigen::Vector3f(0, 0, 1) + pos_vector;
    Eigen::Vector3f up_vector = viewer_pose.rotation() * Eigen::Vector3f(0, -1, 0);

    viewer.setCameraPosition(pos_vector[0], pos_vector[1], pos_vector[2], look_at_vector[0],
        look_at_vector[1], look_at_vector[2], up_vector[0], up_vector[1], up_vector[2]);


}

// -----Main-----
int
main(int argc, char** argv)
{
    //解析命令行参数
    if (pcl::console::find_argument(argc, argv, "-h") >= 0)
    {
        printUsage(argv[0]);
        return 0;
    }
    if (pcl::console::find_argument(argc, argv, "-l") >= 0)
    {
        live_update = true;
        std::cout << "Live update is on.\n";
    }
    if (pcl::console::parse(argc, argv, "-r", angular_resolution) >= 0)
        std::cout << "Setting angular resolution to " << angular_resolution << "deg.\n";
    int tmp_coordinate_frame;
    if (pcl::console::parse(argc, argv, "-c", tmp_coordinate_frame) >= 0)
    {
        coordinate_frame = pcl::RangeImage::CoordinateFrame(tmp_coordinate_frame);
        std::cout << "Using coordinate frame " << (int)coordinate_frame << ".\n";
    }
    angular_resolution = pcl::deg2rad(angular_resolution);

    pcl::PointCloud<PointType>::Ptr point_cloud_ptr(new pcl::PointCloud<PointType>);
    pcl::PointCloud<PointType>& point_cloud = *point_cloud_ptr;
    Eigen::Affine3f scene_sensor_pose(Eigen::Affine3f::Identity());
    std::vector<int> pcd_filename_indices = pcl::console::parse_file_extension_argument(argc, argv, "pcd");
    if (!pcd_filename_indices.empty())
    {
        std::string filename = argv[pcd_filename_indices[0]];
        if (pcl::io::loadPCDFile(filename, point_cloud) == -1)
        {
            std::cout << "Was not able to open file \"" << filename << "\".\n";
            printUsage(argv[0]);
            return 0;
        }
        scene_sensor_pose = Eigen::Affine3f(Eigen::Translation3f(point_cloud.sensor_origin_[0],
            point_cloud.sensor_origin_[1],
            point_cloud.sensor_origin_[2])) *
            Eigen::Affine3f(point_cloud.sensor_orientation_);
    }
    else
    {
        std::cout << "\nNo *.pcd file given => Genarating example point cloud.\n\n";
        for (float x = -0.5f; x <= 0.5f; x += 0.01f)
        {
            for (float y = -0.5f; y <= 0.5f; y += 0.01f)
            {
                PointType point;  point.x = x;  point.y = y;  point.z = 2.0f - y;
                point_cloud.points.push_back(point);
            }
        }
        point_cloud.width = (int)point_cloud.points.size();  point_cloud.height = 1;
    }

    /*
     关于range_image.createFromPointCloud（）参数的解释 （涉及的角度都为弧度为单位） ：
       point_cloud为创建深度图像所需要的点云
      angular_resolution_x深度传感器X方向的角度分辨率
      angular_resolution_y深度传感器Y方向的角度分辨率
       pcl::deg2rad (360.0f)深度传感器的水平最大采样角度
       pcl::deg2rad (180.0f)垂直最大采样角度
       scene_sensor_pose设置的模拟传感器的位姿是一个仿射变换矩阵，默认为4*4的单位矩阵变换
       coordinate_frame定义按照那种坐标系统的习惯  默认为CAMERA_FRAME
       noise_level  获取深度图像深度时，邻近点对查询点距离值的影响水平
       min_range 设置最小的获取距离，小于最小的获取距离的位置为传感器的盲区
       border_size  设置获取深度图像边缘的宽度 默认为0
    */
    float noise_level = 0.0;
    float min_range = 0.0f;
    int border_size = 1;
    boost::shared_ptr<pcl::RangeImage> range_image_ptr(new pcl::RangeImage);
    pcl::RangeImage& range_image = *range_image_ptr;
    range_image.createFromPointCloud(point_cloud, angular_resolution, pcl::deg2rad(360.0f), pcl::deg2rad(180.0f), scene_sensor_pose, coordinate_frame, noise_level, min_range, border_size);
    pcl::visualization::PCLVisualizer viewer("3D Viewer");
    viewer.setBackgroundColor(1, 1, 1);


pcl::visualization::PointCloudColorHandlerCustom<PointType> point_cloud_color_handler (point_cloud_ptr, 0, 0, 0);
  viewer.addPointCloud (point_cloud_ptr, point_cloud_color_handler, "original point cloud");   //添加点云
    //pcl::visualization::PointCloudColorHandlerCustom<pcl::PointWithRange> range_image_color_handler(range_image_ptr, 0, 0, 0);
    //viewer.addPointCloud(range_image_ptr, range_image_color_handler, "range image");
    //viewer.setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "range image");

    viewer.initCameraParameters();
    setViewerPose(viewer, range_image.getTransformationToWorldSystem());
    //显示深度图像
    pcl::visualization::RangeImageVisualizer range_image_widget("Range image");
    range_image_widget.showRangeImage(range_image);
    //主循环
    while (!viewer.wasStopped())
    {
        range_image_widget.spinOnce();
        viewer.spinOnce();
        pcl_sleep(0.01);
        if (live_update)
        {
            scene_sensor_pose = viewer.getViewerPose();
            range_image.createFromPointCloud(point_cloud, angular_resolution, pcl::deg2rad(360.0f), pcl::deg2rad(180.0f), scene_sensor_pose, pcl::RangeImage::LASER_FRAME, noise_level, min_range, border_size);
            range_image_widget.showRangeImage(range_image);
        }
    }
}