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Estimate 3-D geometric transformation from matching point pairs

estimates a 3-D geometric transformation between two sets of 3-D points by
mapping the inliers in the matched points from one set of 3-D points
`tform`

= estimateGeometricTransform3D(`matchedPoints1`

,`matchedPoints2`

,`transformType`

)`matchedPoints1`

to the inliers in the matched points
from the other set of 3-D points `matchedPoints2`

.

`[`

additionally returns a vector specifying each matched point pair as either an
inlier or an outlier using the input arguments from the previous syntax.`tform`

,`inlierIndex`

]
= estimateGeometricTransform3D(___)

`[`

additionally returns a status code indicating whether or not the function could
estimate a transformation and, if not, why it failed. If you do not specify the
`tform`

,`inlierIndex`

,`status`

] = estimateGeometricTransform3D(___)`status`

output, the function instead returns an error
for conditions that cannot produce results.

`[___] = estimateGeometricTransform3D(___, `

specifies additional options using one or more name-value pair arguments in
addition to any combination of arguments from previous syntaxes. For example,
`Name,Value`

)`'Confidence',99`

sets the confidence value for finding the
maximum number of inliers to `99`

.

The function excludes outliers using the M-estimator sample consensus (MSAC) algorithm. The MSAC algorithm is a variant of the random sample consensus (RANSAC) algorithm. Results may not be identical between runs due to the randomized nature of the MSAC algorithm.

[1] Hartley, Richard, and Andrew
Zisserman. *Multiple View Geometry in Computer
Vision*. 2nd ed. Cambridge, UK ; New York: Cambridge University Press,
2003.

[2] Torr, P.H.S., and A.
Zisserman. “MLESAC: A New Robust Estimator with Application to Estimating Image
Geometry.” *Computer Vision and Image Understanding*
78, no. 1 (April 2000): 138–56. https://doi.org/10.1006/cviu.1999.0832.