Register two point clouds using ICP algorithm
returns a rigid transformation that registers a moving point cloud to a fixed
point cloud.tform
= pcregistericp(moving
,fixed
)
The registration algorithm is based on the "iterative closest point" (ICP) algorithm. Best
performance of this iterative process requires adjusting properties for your
data. Consider downsampling point clouds using pcdownsample
before using
pcregistericp
to improve accuracy and efficiency of
registration.
Point cloud normals are required by the registration algorithm
when you select the 'pointToPlane'
metric. Therefore,
if the input point cloud’s Normal
property
is empty, the function fills it. When the function fills the Normal
property,
it uses 6 points to fit the local plane. Six points may not work under
all circumstances. If registration with the 'pointToPlane'
metric
fails, consider calling the pcnormals
function
which allows you to select the number of points to use.
[___] = pcregistericp(
uses additional options specified by one or more moving
,fixed
,Name,Value
)Name,Value
pair arguments.
[1] Chen, Y. and G. Medioni. “Object Modelling by Registration of Multiple Range Images.” Image Vision Computing. Butterworth-Heinemann . Vol. 10, Issue 3, April 1992, pp. 145-155.
[2] Besl, Paul J., N. D. McKay. “A Method for Registration of 3-D Shapes.” IEEE Transactions on Pattern Analysis and Machine Intelligence. Los Alamitos, CA: IEEE Computer Society. Vol. 14, Issue 2, 1992, pp. 239-256.
pcdenoise
| pcdownsample
| pcfitplane
| pcmerge
| pcregistercorr
| pcregistercpd
| pcregisterndt
| pcshow
| pcshowpair
| pctransform