How does 2D PCA sort the cluster point cloud?
Within the lfit_bounding_box functions we take the unordered clusters, run a 2D PCA to then sort them with partial_sort() in order to be able to implement the algorithm seen in the paper "Efficient L-shape Fitting of Laser Scanner Data for Vehicle Pose Estimation". However, what I do not understand is how 2D PCA is being utilized to sort the point cloud. Can anyone explain this to me?
Is this an autoware question?
If so: please label them as such.