In their comments, both says:
/**
* Randomized kd-tree index
*
* Contains the k-d trees and other information for indexing a set of points
* for nearest-neighbor matching.
*/
Anyone can tell me the exact difference of the two Index classes?
Quote from Difference of KDTreeIndexParams vs. KDTreeSingleIndexParams:
Yes, that's exactly it. KDTreeIndex performs approximate NN search, while KDTreeSingleIndex performs exact NN search. The KDTreeSingleIndex is efficient for low dimensional data, for high dimensional data an approximate search algorithm such as the KDTreeIndex will be much faster.
Also from the FLANN manual (flann_manual-1.8.4.pdf):
KDTreeIndexParams
When passing an object of this type the index constructed will consist of a set of randomized kd-trees which will be searched in parallel.
KDTreeSingleIndexParams
When passing an object of this type the index will contain a single kd-tree optimized for searching lower dimen- sionality data (for example 3D point clouds)
Asked: 2015-12-18 08:07:54 -0600
Seen: 972 times
Last updated: Jan 10 '16
