Jon, Paul,

Thanks for the bug report. Can you please submit a ticket with the patch? We would love to integrate it in the next release.

We've been rather quiet about the registration framework, because we're in the process of _completely_ revamping it, 
with the hope to have a faster, more robust framework that works in real-time with the Kinect sensors. If you're 
interested in participating in the discussions and/or helping out, please join pcl-users@ and let's continue there.

Cheers,
Radu.
--
http://pointclouds.org

On 12/10/2010 04:45 PM, Jon Binney wrote:
> I had a similar problem. It turned out in my case that the two point clouds were further apart than the max
> correspondence distance.  This resulted in no correspondences being found, which resulted in a segfault when the ransac
> algorithm tried to choose samples to do the model alignment.
>
> I traced the segfault to the following line in computeModelCoefficients:
>
>      indices_tgt[i] = (*indices_tgt_)[samples[i]];
>
> Adding a check to make sure that returns false when indices_tgt_ has less than samples[i]+1 elements fixed this for me,
> but there is probably a better place to put this check.
>
> -Jon B
>
>
> On Fri, Dec 10, 2010 at 3:57 PM, paulhebert <paulhebert@gmail.com <mailto:paulhebert@gmail.com>> wrote:
>
>
>     Hi All,
>
>     I can't for the life of me, figure what is going wrong. Perhaps, I do not
>     know the structure of PointCloud very well yet but I keep getting a segfault
>     at the last line in "reg.align". I would like to fill in the point cloud
>     with a buffer of floats/doubles and then run ICP on the two cloud points. Is
>     this the right way to do it? It seems to work if I use PCD files but not
>     when I manually input data like below. Hope someone can help.
>
>
>         // Fill in the model cloud data
>         model.width    = modelN;
>         model.height   = 1;
>         model.is_dense = false;
>         model.points.resize (model.width * model.height);
>
>         for (size_t i = 0; i < model.points.size (); i++)
>         {
>             model.points[i].x = (float)modelPointsT[3*i + 0];
>             model.points[i].y = (float)modelPointsT[3*i + 1];
>             model.points[i].z = (float)modelPointsT[3*i + 2];
>         }
>        // Fill in the model cloud data
>         data.width    = dataN;
>         data.height   = 1;
>         data.is_dense = false;
>         data.points.resize (data.width * data.height);
>
>         for (size_t i = 0; i < data.points.size (); i++)
>         {
>             data.points[i].x = (float)dataPointsT[3*i + 0] + 5;
>             data.points[i].y = (float)dataPointsT[3*i + 1];
>             data.points[i].z = (float)dataPointsT[3*i + 2];
>         }
>
>         pcl::PointCloud<pcl::PointXYZ> output;
>
>         pcl::IterativeClosestPointNonLinear<pcl::PointXYZ, pcl::PointXYZ> reg;
>
>         reg.setMaxCorrespondenceDistance (0.1);
>         reg.setTransformationEpsilon (1e-6);
>         reg.setMaximumIterations (50);
>
>         reg.setInputCloud(boost::make_shared<const
>     pcl::PointCloud<pcl::PointXYZ> > (data));
>         reg.setInputTarget(boost::make_shared<const
>     pcl::PointCloud<pcl::PointXYZ> > (model));
>         Eigen3::Matrix4f transform;
>         //reg.computeTransformation(output);
>         //reg.estimateRigidTransformationLM(data,model,transform);
>         printf("Done\n");
>         reg.align(output);
>
>
>     --
>     View this message in context: http://ros-users.122217.n3.nabble.com/ICP-PCL-with-foreign-data-tp2066643p2066643.html
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