How to get from a opencv Mat pointcloud to a pcl::pointcloud? The color is not important for me only the points itself.
How to convert cv::Mat to pcl::pointcloud
Asked Answered
you can do this like:
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;
}
And also the otherway
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;
}
This is for unorganized cloud only. –
Cocke
To convert from a range image captured by a Kinect sensor and represented by depthMat to a pcl::PointCloud you can try this function. The calibration parameters are those used here.
{
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;
}
}
This is a slow function that can be speed-up with less multiplications and more outside of the for loop. Doing fx_d and fy_d before the function 1/fx_d and 1/fy_d and then multiply that. Try it ! –
Barbell
@MartijnvanWezel Thanks for the comment. I edited the answer. –
Sandler
points.push_back
maybe we can define point cloud with predefined size based on image size to not reallocated memory? –
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