Fit sphere to 3-D point cloud

`model = pcfitsphere(ptCloudIn,maxDistance)`

```
[model,inlierIndices,outlierIndices]
= pcfitsphere(ptCloudIn,maxDistance)
```

```
[___,meanError] =
pcfitsphere(ptCloudIn,maxDistance)
```

`[___] = pcfitsphere(___,Name,Value)`

fits
a sphere to a point cloud tha has a maximum allowable distance from
an inlier point to the sphere. The function returns a geometrical
model that describes the sphere.`model`

= pcfitsphere(`ptCloudIn`

,`maxDistance`

)

This function uses the M-estimator SAmple Consensus (MSAC) algorithm to find the sphere. The MSAC algorithm is a variant of the RANdom SAmple Consensus (RANSAC) algorithm.

`[`

additionally
returns linear indices to the inlier and outlier points in the point
cloud input.`model`

,`inlierIndices`

,`outlierIndices`

]
= pcfitsphere(`ptCloudIn`

,`maxDistance`

)

`[___,`

additionally
returns the mean error of the distance of inlier points to the model,
using any of the preceding syntaxes.`meanError`

] =
pcfitsphere(`ptCloudIn`

,`maxDistance`

)

`[___] = pcfitsphere(___,`

uses
additional options specified by one or more `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`

| `pcfitplane`

| `pcmerge`

| `pcplayer`

| `pcread`

| `pcregistericp`

| `pcshow`

| `pctransform`

| `pcwrite`

| `planeModel`

| `pointCloud`