Currently included are:
pointCloud class | a Matlab class to read, manipulate and write point clouds |
globalICP class | a Matlab class to optimize the alignment of many point clouds with the ICP algorithm |
D:\MyMatlabCode\pointCloudTools
.addpath(genpath('D:\MyMatlabCode\pointCloudTools'));
pc = pointCloud('Lion.xyz'); pc.plot;
This is a class for processing point clouds of any size in Matlab. It provides many functions to read, manipulate, and write point clouds. Check out some of the functionality in this introductory tutorial.
Class methods:
pointCloud | Import of point cloud data. |
select | Select a subset of points. |
plot | Plot of point cloud. |
normals | Compute normal vectors of activated points. |
plotNormals | Plot normal vectors of point cloud in 3d. |
info | Report informations about the point cloud to the command window. |
transform | Coordinate transformation of point cloud. |
export | Export activated points to a file. |
save | Save point cloud object as mat file. |
reconstruct | Reconstruct object only with active points. |
getVoxelHull | Compute the voxel hull of a point cloud. |
addAttribute | Add an attribute to the object. |
With the globalICP class the alignment of two or more point clouds can be refined by the Iterative Closest Point (ICP) algorithm. A prerequisite for this is an approximate alignment of the point clouds.
Class methods:
globalICP | Constructor method for global ICP class. |
runICP | Run ICP algorithm. |
addPC | Add a point cloud to globalICP object. |
loadPC | Load point cloud to workspace. |
exportPC | Export a point cloud. |
plot | Plot all added point clouds. |
ICP -inFiles demodata\lionscan*approx.xyz -UniformSamplingDistance 2 -PlaneSearchRadius 2 -Plot 1
Contact: philipp.glira@gmail.com (Google Scholar)