如何将cv::Mat转换为pcl::pointcloud

Question

如何从OpenCV Mat点云获取PCL::Pointcloud？颜色对我来说并不重要，只关注点本身。

- Martijn van Wezel

Answer 1

你可以像这样做：

pcl::PointCloud<pcl::PointXYZ>::Ptr SimpleOpenNIViewer::MatToPoinXYZ(cv::Mat OpencVPointCloud)
         {
             /*
             *  Function: Get from a Mat to pcl pointcloud datatype
             *  In: cv::Mat
             *  Out: pcl::PointCloud
             */

             //char pr=100, pg=100, pb=100;
             pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_ptr(new pcl::PointCloud<pcl::PointXYZ>);//(new pcl::pointcloud<pcl::pointXYZ>);

             for(int i=0;i<OpencVPointCloud.cols;i++)
             {
                //std::cout<<i<<endl;

                pcl::PointXYZ point;
                point.x = OpencVPointCloud.at<float>(0,i);
                point.y = OpencVPointCloud.at<float>(1,i);
                point.z = OpencVPointCloud.at<float>(2,i);

                // when color needs to be added:
                //uint32_t rgb = (static_cast<uint32_t>(pr) << 16 | static_cast<uint32_t>(pg) << 8 | static_cast<uint32_t>(pb));
                //point.rgb = *reinterpret_cast<float*>(&rgb);

                point_cloud_ptr -> points.push_back(point);


             }
             point_cloud_ptr->width = (int)point_cloud_ptr->points.size();
             point_cloud_ptr->height = 1;

             return point_cloud_ptr;

         }

同时还有另一种方式

 cv::Mat MVW_ICP::PoinXYZToMat(pcl::PointCloud<pcl::PointXYZ>::Ptr point_cloud_ptr){

     cv::Mat OpenCVPointCloud(3, point_cloud_ptr->points.size(), CV_64FC1);
     for(int i=0; i < point_cloud_ptr->points.size();i++){
        OpenCVPointCloud.at<double>(0,i) = point_cloud_ptr->points.at(i).x;
        OpenCVPointCloud.at<double>(1,i) = point_cloud_ptr->points.at(i).y;
        OpenCVPointCloud.at<double>(2,i) = point_cloud_ptr->points.at(i).z;
    }

    return OpenCVPointCloud;
}

- Martijn van Wezel

---

这仅适用于非组织化云。 - zhangxaochen

Answer 2

要将由Kinect传感器捕获的深度图像(depthMat)转换为pcl::PointCloud，您可以尝试使用此函数。 标定参数是这里使用的参数。

{
    pcl::PointCloud<pcl::PointXYZ>::Ptr MatToPoinXYZ(cv::Mat depthMat)
{
    pcl::PointCloud<pcl::PointXYZ>::Ptr ptCloud (new pcl::PointCloud<pcl::PointXYZ>);

// calibration parameters
    float const fx_d = 5.9421434211923247e+02;
    float const fy_d = 5.9104053696870778e+02;
    float const cx_d = 3.3930780975300314e+02;
    float const cy_d = 2.4273913761751615e+02;

    unsigned char* p = depthMat.data;
    for (int i = 0; i<depthMat.rows; i++)
    {
        for (int j = 0; j < depthMat.cols; j++)
        {
            float z = static_cast<float>(*p);
            pcl::PointXYZ point;
            point.z = 0.001 * z;
            point.x = point.z*(j - cx_d)  / fx_d;
            point.y = point.z *(cy_d - i) / fy_d;
            ptCloud->points.push_back(point);
            ++p;
        }
    }
    ptCloud->width = (int)depthMat.cols; 
    ptCloud->height = (int)depthMat.rows; 

    return ptCloud;

}
}

- Mohamed Hasan

---

这是一个较慢的函数，可以通过减少乘法次数并将其移出for循环来加速。在函数1/fx_d和1/fy_d之前执行fx_d和fy_d，然后进行乘法运算。试一下吧！ - Martijn van Wezel

@MartijnvanWezel 感谢您的评论。我编辑了答案。 - Mohamed Hasan

也许我们可以根据图像大小定义预定义大小的点云，以避免重新分配内存，使用 points.push_back？ - mrgloom