image thumbnail

k-D tree

version 1.2.0.0 (15.4 KB) by Guy Shechter
Perform closest point search or range query using a k-D tree implementation.

16.4K Downloads

Updated 29 Oct 2013

View License

This distribution contains the KDTREE, KDTREEIDX, and KDRANGEQUERY functions.

-----
KDTREE Find closest points using a k-D tree.

CP = KDTREE( REFERENCE, MODEL ) finds the closest points in
REFERENCE for each point in MODEL. The search is performed in an efficient manner by building a k-D tree from the datapoints in REFERENCE, and querying the tree for each datapoint in MODEL.

IDX = KDTREEIDX( REFERENCE, MODEL ) finds the closest points in REFERENCE for each point in MODEL. The search is performed in an efficient manner by building a k-D tree from the datapoints in REFERENCE, and querying the tree for each datapoint in MODEL.

PTS = KDRANGEQUERY( ROOT, QUERYPT, DISTLIM ) finds all the points stored in the k-D tree ROOT that are within DISTLIM units from the QUERYPT. Proximity is quantified using a D-dimensional Euclidean (2-norm) distance.
-----

Two demo scripts are provided (kdtree_demo.m & kdrange_demo.m).

You will need to compile the code in the kdtree/src library using the
MATLAB mex compiler. Place the compiled mex files in the kdtree/lib directory. Finally, add the kdtree/lib directory to your MATLAB path.

** Refer to the README file for more detailed instructions.

Cite As

Guy Shechter (2021). k-D tree (https://www.mathworks.com/matlabcentral/fileexchange/4586-k-d-tree), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2013b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!