In the PCL tutorial, we can learn how to segment a plane and extract the Euclidean cluster point clouds. So now, after I used the
pcl::EuclideanClusterExtraction algorithm. I need the centroid or the mean position of each cluster.
pcl::EuclideanClusterExtraction I need to calculate the centroid with the for loops. After my search I found out the
pcl::Kmeans which provides directly a function
get_centroids() to get the centroids of the clusters: https://pointclouds.org/documentation/classpcl_1_1_kmeans.html#a8788bd4098ea370e018119fc516a5eb4
Now, I’m a little bit confused. What is the real application different between
pcl::Kmeans? After analysing the source code,
pcl::EuclideanClusterExtraction provides us clusters based on three parameters.
pcl::Kmeans is used if we determine how many clusters we want to generate, because of the arguments in the constructor
Kmeans (unsigned int num_points, unsigned int num_dimensions).
Is that true? Is there any other cases?
Source: Windows Questions C++