[点云分割] 使用 ModelOutlierRemoving 过滤点云

使用已知系数的几何模型，例如平面或球体，对一个点云进行滤波操作。

#include <iostream>
#include <pcl/point_types.h>
#include <pcl/filters/model_outlier_removal.h>

int main ()
{
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_sphere_filtered (new pcl::PointCloud<pcl::PointXYZ>);

    // 1. Generate cloud data
    std::size_t noise_size = 5;
    std::size_t sphere_data_size = 10;
    cloud->width = noise_size + sphere_data_size;
    cloud->height = 1;
    cloud->points.resize (cloud->width * cloud->height);

    // 1.1 Add noise
    for (std::size_t i = 0; i < noise_size; ++i)
    {
        (*cloud)[i].x = 1024 * rand () / (RAND_MAX + 1.0f);
        (*cloud)[i].y = 1024 * rand () / (RAND_MAX + 1.0f);
        (*cloud)[i].z = 1024 * rand () / (RAND_MAX + 1.0f);
     }

    // 1.2 Add sphere:
    double rand_x1 = 1;
    double rand_x2 = 1;
    for (std::size_t i = noise_size; i < (noise_size + sphere_data_size); ++i)
    {
        // See: http://mathworld.wolfram.com/SpherePointPicking.html
        while (pow (rand_x1, 2) + pow (rand_x2, 2) >= 1)
            {
            rand_x1 = (rand () % 100) / (50.0f) - 1;
            rand_x2 = (rand () % 100) / (50.0f) - 1;
            }
        double pre_calc = sqrt (1 - pow (rand_x1, 2) - pow (rand_x2, 2));
        (*cloud)[i].x = 2 * rand_x1 * pre_calc;
        (*cloud)[i].y = 2 * rand_x2 * pre_calc;
        (*cloud)[i].z = 1 - 2 * (pow (rand_x1, 2) + pow (rand_x2, 2));
        rand_x1 = 1;
        rand_x2 = 1;
        }

        std::cerr << "Cloud before filtering: " << std::endl;
    for (const auto& point: *cloud)
        std::cout << "    " << point.x << " " << point.y << " " << point.z << std::endl;

    // 2. filter sphere:
    // 2.1 generate model:
    // modelparameter for this sphere:
    // position.x: 0, position.y: 0, position.z:0, radius: 1
    pcl::ModelCoefficients sphere_coeff;
    sphere_coeff.values.resize (4);
    sphere_coeff.values[0] = 0;
    sphere_coeff.values[1] = 0;
    sphere_coeff.values[2] = 0;
    sphere_coeff.values[3] = 1;

    pcl::ModelOutlierRemoval<pcl::PointXYZ> sphere_filter;
    sphere_filter.setModelCoefficients (sphere_coeff);
    sphere_filter.setThreshold (0.05);
    sphere_filter.setModelType (pcl::SACMODEL_SPHERE);
    sphere_filter.setInputCloud (cloud);
    sphere_filter.filter (*cloud_sphere_filtered);

    std::cerr << "Sphere after filtering: " << std::endl;
    for (const auto& point: *cloud_sphere_filtered)
    std::cout << "    " << point.x << " " << point.y << " " << point.z << std::endl;

    return (0);
}