CovarianceSampling always return the first n point
I have an organized point cloud grabbed from an RGB-D sensor. I am trying to
apply `CovarianceSampling` on it. However, I am getting very strange result
which is the first N point of the cloud.
The code I am using:
//Grab the point cloud(point_cloud) and compute the
pcl::CovarianceSampling<pcl::PointXYZ, pcl::Normal> covariance_sampling;
This does not happen if I use another sampler such as `NormalSpaceSampling`.
Re: CovarianceSampling always return the first n point
Disclaimer: I'm assuming you meant to write:
However, I am getting very strange result
which are the first N points of the cloud.
It does sound weird, although there's nothing which prevents it from
doing so other than condition
It selects the points such that the resulting cloud is as
stable as possible for being registered (against a copy of
itself) with ICP. The algorithm adds points to the resulting
cloud incrementally, while trying to keep all the 6 eigenvalues
of the covariance matrix as close to each other as possible.
I would be surprising if these were always the first N samples you
Try to come up with a simple example we can all reproduce and open
an issue in the issue tracker please.