I don't recommend using MLESAC, RMSAC, or RRANSAC for solving the table_lms400 planarity model problem, at least not in
their current form. All these methods are only useful in situations where most of the data samples belong to the model
(80%+ for example), and a fast outlier rejection algorithm is needed. In the table_lms400 case, the model constitutes
only roughly half of the scene, and that can cause problems. That's not to say that things couldn't be improved of
course. Patches... welcome ;)
I would use RANSAC, LMEDS and MSAC for problems such as table_lms400, as they are more robust.
Cheers,
Radu.
On 07/27/2010 05:42 AM, PinakiBanerjee wrote:
>
> Hi, I tried using MLESAC for SACMODEL_PLANE for segmentation of point cloud
> dataset : table_scene_lms400.pcd from ROS. Unfortunately it fails to detect
> the planes as can be seen in the image. This is the result obtained for 2000
> iterations :
>
> http://ros-users.122217.n3.nabble.com/file/n999095/MLESAC_2000.png
>
> Color convention : Green: Plane 1, Red: Plane 2., White: Remaining pixels.
>
>
> Although the result of RANSAC for 50 iteration is accpetable as can be seen
> below:
>
> http://ros-users.122217.n3.nabble.com/file/n999095/RANSAC_50.png
>
>
> The code i used to prodece it is given below:
>
> #include "pcl/io/pcd_io.h"
> #include "pcl/point_types.h"
>
> #include "pcl/sample_consensus/method_types.h"
> #include "pcl/sample_consensus/model_types.h"
> #include "pcl/segmentation/sac_segmentation.h"
> #include "fstream"
>
> using namespace std;
>
> /* ---[ */
> int
> main (int argc, char** argv)
> {
>
> //-----------------------Reading the data-----------------------------
> sensor_msgs::PointCloud2 cloud_blob;
> pcl::PointCloud<pcl::PointXYZ> cloud;
>
> if (pcl::io::loadPCDFile ("table_scene_lms400.pcd", cloud_blob) == -1)
> {
> ROS_ERROR ("Couldn't read file test_pcd.pcd");
> return (-1);
> }
> ROS_INFO ("Loaded %d data points from test_pcd.pcd with the following
> fields: %s", (int)(cloud_blob.width * cloud_blob.height), pcl::getFieldsList
> (cloud_blob).c_str ());
>
> // Convert to the templated message type
> point_cloud::fromMsg (cloud_blob, cloud);
>
>
> //-----------------------Appliying the segmentation
> algorithm-------------------------
>
> pcl::ModelCoefficients coefficients;
> pcl::PointIndices inliers;
> // Create the segmentation object
> pcl::SACSegmentation<pcl::PointXYZ> seg;
> // Optional
> seg.setOptimizeCoefficients (true);
> // Mandatory
> seg.setModelType (pcl::SACMODEL_PLANE);
> seg.setMethodType (pcl::SAC_MLESAC);
> seg.setDistanceThreshold (0.01);
> seg.setMaxIterations (2000);
> seg.setInputCloud (boost::make_shared<pcl::PointCloud<pcl::PointXYZ>
>> (cloud));
>
> time_t tstart, tend;
>
> tstart = time(NULL);
> seg.segment (inliers, coefficients);
> tend = time(NULL);
> ROS_INFO("Segmentation 1 Time elapsed %f", difftime(tend,tstart));
>
> if (inliers.indices.size () == 0)
> {
> ROS_ERROR ("Could not estimate a planar model for the given dataset.");
> return (-1);
> }
> ROS_INFO ("Done segmentation of initial cloud");
> ROS_INFO("No. of Inliers1 : %d",inliers.indices.size ());
>
> //--------------------------writing the
> inliers------------------------------
>
>
> ofstream SaveFile("inliers1_table_MLESAC_2000.txt");
>
> for (size_t i = 0; i< inliers.indices.size (); ++i){
> SaveFile<< cloud.points[inliers.indices[i]].x<< " "<<
> cloud.points[inliers.indices[i]].y<< ""
> <<cloud.points[inliers.indices[i]].z<< endl;
> }
>
> SaveFile.close();
>
> ROS_INFO ("Results of segmentation of initial cloud written");
>
> //---------------------------------------------------------------------------
>
> pcl::PointCloud<pcl::PointXYZ> cloud1;
>
> cloud1.width = cloud.width - inliers.indices.size();
> cloud1.height = 1;
> cloud1.points.resize (cloud1.width * cloud1.height);
>
> int first,mid,last,val,key,index;
> int a = 0;
> for(index= 0 ; index<cloud.width; index++ ){
>
> val=-1;
> first=0;
> last =inliers.indices.size()-1;
> key=index;
>
> while (first<= last) {
> mid = (first + last) / 2; // compute mid point.
> if (key> inliers.indices[mid])
> first = mid + 1; // repeat search in top half.
> else if (key< inliers.indices[mid])
> last = mid - 1; // repeat search in bottom half.
> else{
> val=0; // found it. return position /////
> break;
> }
> }
>
> if(val==-1){
>
> cloud1.points[a].x = cloud.points[index].x;
> cloud1.points[a].y = cloud.points[index].y;
> cloud1.points[a].z = cloud.points[index].z;
> a++;
> }
> }
> cout<< a<< " = "<< cloud1.width;
> ROS_INFO ("Cloud2 created successfully");
>
> //--------------------------writing the modified
> cloud------------------------------
>
>
> ofstream SaveFile3("cloud2_table_MLESAC_2000.txt");
>
> for (size_t i = 0; i< cloud1.width; ++i){
> SaveFile3<< cloud.points[i].x<< " "<< cloud.points[i].y<< ""
> <<cloud.points[i].z<< endl;
> }
>
> SaveFile3.close();
>
> ROS_INFO ("cloud2 written");
>
>
> //-----------------------Appliying the segmentation algorithm on the
> modified cloud-------------------------
>
>
>
>
> seg.setInputCloud (boost::make_shared<pcl::PointCloud<pcl::PointXYZ>
>> (cloud1));
> pcl::PointIndices inliers1;
>
> tstart = time(0);
> seg.segment (inliers1, coefficients);
> tend = time(0);
>
> ROS_INFO("Segmentation 2 Time elapsed %f", difftime(tend,tstart));
>
> if (inliers1.indices.size () == 0)
> {
> ROS_ERROR ("Could not estimate a planar model for the given dataset.");
> return (-1);
> }
>
> ROS_INFO("No. of Inliers2 : %d",inliers1.indices.size ());
> ROS_INFO ("Cloud2 segmented successfully");
> //--------------------------writing the
> inliers------------------------------//
>
>
> ofstream SaveFile1("inliers2_table_MLESAC_2000.txt");
>
> for (size_t i = 0; i< inliers1.indices.size (); ++i)
> SaveFile1<< cloud1.points[inliers1.indices[i]].x<< " "<<
> cloud1.points[inliers1.indices[i]].y<< ""
> <<cloud1.points[inliers1.indices[i]].z<< endl;
>
> SaveFile1.close();
>
> ROS_INFO ("Cloud2 written successfully");
> //---------------------------------------------------------------------------
>
> return (0);
> }
> /* ]--- */
>
>
> Is it a bug in the program? or am i missing some thing? Please help.
--
| Radu Bogdan Rusu | http://rbrusu.com/
,%20and%20a%20fast%20outlier%20rejection%20algorithm%20is%20needed.%20In%20the%20table_lms400%20case,%20the%20model%20constitutes%20%0A>%20only%20roughly%20half%20of%20the%20scene,%20and%20that%20can%20cause%20problems.%20That's%20not%20to%20say%20that%20things%20couldn't%20be%20improved%20of%20%0A>%20course.%20Patches...%20welcome%20;)%0A>%20%0A>%20I%20would%20use%20RANSAC,%20LMEDS%20and%20MSAC%20for%20problems%20such%20as%20table_lms400,%20as%20they%20are%20more%20robust.%0A>%20%0A>%20Cheers,%0A>%20Radu.%0A>%20%0A>%20On%2007/27/2010%2005:42%20AM,%20PinakiBanerjee%20wrote:%0A>%20>%0A>%20>%20Hi,%20I%20tried%20using%20MLESAC%20for%20SACMODEL_PLANE%20for%20segmentation%20of%20point%20cloud%0A>%20>%20dataset%20:%20table_scene_lms400.pcd%20from%20ROS.%20Unfortunately%20it%20fails%20to%20detect%0A>%20>%20the%20planes%20as%20can%20be%20seen%20in%20the%20image.%20This%20is%20the%20result%20obtained%20for%202000%0A>%20>%20iterations%20:%0A>%20>%0A>%20>%20http://ros-users.122217.n3.nabble.com/file/n999095/MLESAC_2000.png%0A>%20>%0A>%20>%20Color%20convention%20:%20Green:%20Plane%201,%20Red:%20Plane%202.,%20White:%20Remaining%20pixels.%0A>%20>%0A>%20>%0A>%20>%20Although%20the%20result%20of%20RANSAC%20for%2050%20iteration%20is%20accpetable%20as%20can%20be%20seen%0A>%20>%20below:%0A>%20>%0A>%20>%20http://ros-users.122217.n3.nabble.com/file/n999095/RANSAC_50.png%0A>%20>%0A>%20>%0A>%20>%20The%20code%20i%20used%20to%20prodece%20it%20is%20given%20below:%0A>%20>%0A>%20>%20#include%20%22pcl/io/pcd_io.h%22%0A>%20>%20#include%20%22pcl/point_types.h%22%0A>%20>%0A>%20>%20#include%20%22pcl/sample_consensus/method_types.h%22%0A>%20>%20#include%20%22pcl/sample_consensus/model_types.h%22%0A>%20>%20#include%20%22pcl/segmentation/sac_segmentation.h%22%0A>%20>%20#include%20%22fstream%22%0A>%20>%0A>%20>%20using%20namespace%20std;%0A>%20>%0A>%20>%0A>%20>%0A>%20>%0A>%20>%0A>%20>%0A>%20>%20//-----------------------Appliying%20the%20segmentation%0A>%20>%20algorithm-------------------------%0A>%20>%0A>%20>%0A>%20>%20time_t%20tstart,%20tend;%0A>%20>%0A>%20>%0A>%20>%0A>%20>%20//--------------------------writing%20the%0A>%20>%20inliers------------------------------%0A>%20>%0A>%20>%0A>%20>%20ofstream%20SaveFile(%22inliers1_table_MLESAC_2000.txt%22);%0A>%20>%0A>%20>%20for%20(size_t%20i%20=%200;%20i<%20%20inliers.indices.size%20();%20++i)%7B%0A>%20>%20SaveFile<<%20%20cloud.points%5Binliers.indices%5Bi%5D%5D.x<<%20%20%22%20%22<<%0A>%20>%20cloud.points%5Binliers.indices%5Bi%5D%5D.y<<%20%20%22%22%0A>%20>%20<<cloud.points%5Binliers.indices%5Bi%5D%5D.z<<%20%20endl;%0A>%20>%20%7D%0A>%20>%0A>%20>%20SaveFile.close();%0A>%20>%0A>%20>%20ROS_INFO%20(%22Results%20of%20segmentation%20of%20initial%20cloud%20written%22);%0A>%20>%0A>%20>%20//---------------------------------------------------------------------------%0A>%20>%0A>%20>%20pcl::PointCloud<pcl::PointXYZ>%20%20cloud1;%0A>%20>%0A>%20>%20cloud1.width%20=%20cloud.width%20-%20inliers.indices.size();%0A>%20>%20cloud1.height%20=%201;%0A>%20>%20cloud1.points.resize%20(cloud1.width%20*%20cloud1.height);%0A>%20>%0A>%20>%20int%20first,mid,last,val,key,index;%0A>%20>%20int%20a%20=%200;%0A>%20>%20for(index=%200%20;%20index<cloud.width;%20index++%20)%7B%0A>%20>%0A>%20>%20val=-1;%0A>%20>%20first=0;%0A>%20>%20last%20=inliers.indices.size()-1;%0A>%20>%20key=index;%0A>%20>%0A>%20>%0A>%20>%20%20%20%20%20%0A>%20>%0A>%20>%20//--------------------------writing%20the%20modified%0A>%20>%20cloud------------------------------%0A>%20>%0A>%20>%0A>%20>%20ofstream%20SaveFile3(%22cloud2_table_MLESAC_2000.txt%22);%0A>%20>%0A>%20>%20for%20(size_t%20i%20=%200;%20i<%20%20cloud1.width;%20++i)%7B%0A>%20>%20SaveFile3<<%20%20cloud.points%5Bi%5D.x<<%20%20%22%20%22<<%20%20cloud.points%5Bi%5D.y<<%20%20%22%22%0A>%20>%20<<cloud.points%5Bi%5D.z<<%20%20endl;%0A>%20>%20%7D%0A>%20>%0A>%20>%20SaveFile3.close();%0A>%20>%0A>%20>%20ROS_INFO%20(%22cloud2%20written%22);%0A>%20>%0A>%20>%0A>%20>%20//-----------------------Appliying%20the%20segmentation%20algorithm%20on%20the%0A>%20>%20modified%20cloud-------------------------%0A>%20>%0A>%20>%0A>%20>%0A>%20>%0A>%20>%20%20%20%20%20%0A>%20>%0A>%20>%20ROS_INFO(%22Segmentation%202%20Time%20elapsed%20%f%22,%20difftime(tend,tstart));%0A>%20>%0A>%20>%0A>%20>%20%20%20ROS_INFO(%22No.%20of%20Inliers2%20:%20%20%d%22,inliers1.indices.size%20());%0A>%20>%20ROS_INFO%20(%22Cloud2%20segmented%20successfully%22);%0A>%20>%20//--------------------------writing%20the%0A>%20>%20inliers------------------------------//%0A>%20>%0A>%20>%0A>%20>%20ofstream%20SaveFile1(%22inliers2_table_MLESAC_2000.txt%22);%0A>%20>%0A>%20>%20for%20(size_t%20i%20=%200;%20i<%20%20inliers1.indices.size%20();%20++i)%0A>%20>%20SaveFile1<<%20%20cloud1.points%5Binliers1.indices%5Bi%5D%5D.x<<%20%20%22%20%22<<%0A>%20>%20cloud1.points%5Binliers1.indices%5Bi%5D%5D.y<<%20%20%22%22%0A>%20>%20<<cloud1.points%5Binliers1.indices%5Bi%5D%5D.z<<%20%20endl;%0A>%20>%0A>%20>%20SaveFile1.close();%0A>%20>%0A>%20>%20ROS_INFO%20(%22Cloud2%20written%20successfully%22);%0A>%20>%20//---------------------------------------------------------------------------%0A>%20>%0A>%20>%0A>%20>%0A>%20>%20Is%20it%20a%20bug%20in%20the%20program?%20or%20am%20i%20missing%20some%20thing?%20Please%20help.%0A>%20%0A>%20--%20%0A>%20%7C%20Radu%20Bogdan%20Rusu%20%7C%20http://rbrusu.com/%0A>%20%0A>%20 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