Fit plane to 3-D point cloud
model = pcfitplane(ptCloudIn,maxDistance)
model = pcfitplane(ptCloudIn,maxDistance,referenceVector)
model = pcfitplane(ptCloudIn,maxDistance,referenceVector,maxAngularDistance)
[model,inlierIndices,outlierIndices]
= pcfitplane(ptCloudIn,maxDistance)
[___,meanError] =
pcfitplane(ptCloudIn,maxDistance)
[___] = pcfitplane(ptCloudIn,maxDistance,Name,Value)
fits
a plane to a point cloud that has a maximum allowable distance from
an inlier point to the plane. The function returns a geometrical model
that describes the plane.model
= pcfitplane(ptCloudIn
,maxDistance
)
This function uses the M-estimator SAmple Consensus (MSAC) algorithm to find the plane. The MSAC algorithm is a variant of the RANdom SAmple Consensus (RANSAC) algorithm.
fits
a plane to a point cloud that has additional orientation constraints
specified by the 1-by-3 model
= pcfitplane(ptCloudIn
,maxDistance
,referenceVector
)referenceVector
input.
fits
a plane to a point cloud that has a specified maximum angular distance.model
= pcfitplane(ptCloudIn
,maxDistance
,referenceVector
,maxAngularDistance
)
[
additionally
returns the linear indices to the inlier and outlier points in the
point cloud input.model
,inlierIndices
,outlierIndices
]
= pcfitplane(ptCloudIn
,maxDistance
)
[___,
additionally
returns the mean error of the distance of inlier points to the model,
using any of the preceding syntaxes.meanError
] =
pcfitplane(ptCloudIn
,maxDistance
)
[___] = pcfitplane(
uses
additional options specified by one or more ptCloudIn
,maxDistance
,Name,Value
)Name,Value
pair
arguments.
[1] Torr, P. H. S., and A. Zisserman. “MLESAC: A New Robust Estimator with Application to Estimating Image Geometry.” Computer Vision and Image Understanding. 2000.
affine3d
| pcdenoise
| pcfitcylinder
| pcfitsphere
| pcmerge
| pcplayer
| pcread
| pcregistericp
| pcshow
| pctransform
| pcwrite
| planeModel
| pointCloud