Opencv 如何将cv::Mat转换为pcl::pointcloud
如何从opencv Mat pointcloud到pcl::pointcloud?颜色对我来说并不重要,只是点本身 您可以这样做:Opencv 如何将cv::Mat转换为pcl::pointcloud,opencv,converter,point-cloud-library,Opencv,Converter,Point Cloud Library,如何从opencv Mat pointcloud到pcl::pointcloud?颜色对我来说并不重要,只是点本身 您可以这样做: pcl::PointCloud<pcl::PointXYZ>::Ptr SimpleOpenNIViewer::MatToPoinXYZ(cv::Mat OpencVPointCloud) { /* * Function: Get from a Mat to pcl pointclo
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;
}
pcl::PointCloud::Ptr SimplePointInviewer::Mattopinxyz(cv::Mat OpencVPointCloud)
{
/*
*函数:从Mat获取到pcl pointcloud数据类型
*In:cv::Mat
*Out:pcl::PointCloud
*/
//字符pr=100,pg=100,pb=100;
pcl::PointCloud::Ptr point_cloud_Ptr(新的pcl::PointCloud);//(新的pcl::PointCloud);
对于(i=0;i点在(i).x;
OpenCVPointCloud.at(1,i)=point_cloud_ptr->points.at(i).y;
OpenCVPointCloud.at(2,i)=point_cloud_ptr->points.at(i).z;
}
返回OpenCVPointCloud;
}
要将由Kinect传感器捕获并由depthMat表示的距离图像转换为pcl::PointCloud,您可以尝试此功能。校准参数是使用的参数
{
pcl::PointCloud::Ptr Mattopinxyz(cv::Mat depthMat)
{
pcl::PointCloud::Ptr ptCloud(新的pcl::PointCloud);
//校准参数
浮动常数fx_d=5.9421434211923247e+02;
浮球常数fy_d=5.9104053696870778e+02;
浮点数cx_d=3.39307809750314e+02;
浮子常数cy_d=2.4273913761751615e+02;
无符号字符*p=depthMat.data;
对于(int i=0;i点向后推(点);
++p;
}
}
ptCloud->width=(int)depthMat.cols;
ptCloud->height=(int)depthMat.rows;
返回ptCloud;
}
}
这是一个缓慢的函数,可以通过较少的乘法和更多的for循环之外的运算来加速。在函数1/fx\u d和1/fy\u d之前执行fx\u d和fy\u d,然后再进行乘法。试试吧!@MartijnvanWezel谢谢你的评论。我编辑了答案。点。向后推
也许我们可以定义预定义大小的点云基于图像大小不重新分配内存?这仅适用于无组织的云。
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;
}
{
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;
}
}