Note: This page has been translated by MathWorks. Please click here

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

Estimate fundamental matrix from corresponding points in stereo images

- example
`estimateFundamentalMatrix`

- example
`F = estimateFundamentalMatrix(matchedPoints1,matchedPoints2)`

`[F,inliersIndex] = estimateFundamentalMatrix(matchedPoints1,matchedPoints2)`

`[F,inliersIndex,status] = estimateFundamentalMatrix(matchedPoints1,matchedPoints2)`

`[F,inliersIndex,status] = estimateFundamentalMatrix(matchedPoints1,matchedPoints2,Name,Value)`

`estimateFundamentalMatrix`

estimates the
fundamental matrix from corresponding points in stereo images. This
function can be configured to use all corresponding points or to exclude
outliers. You can exclude outliers by using a robust estimation technique
such as random-sample consensus (RANSAC). When you use robust estimation,
results may not be identical between runs because of the randomized
nature of the algorithm.

returns
the 3-by-3 fundamental matrix, `F`

= estimateFundamentalMatrix(`matchedPoints1`

,`matchedPoints2`

)`F`

, using the least
median of squares (LMedS) method. The input points can be *M*-by-2
matrices of *M* number of [x y] coordinates, or `SURFPoints`

, `MSERRegions`

, or `cornerPoints`

object.

`[`

additionally
returns logical indices, `F`

,`inliersIndex`

]
= estimateFundamentalMatrix(`matchedPoints1`

,`matchedPoints2`

)`inliersIndex`

, for the
inliers used to compute the fundamental matrix. The `inliersIndex`

output
is an *M*-by-1 vector. The function sets the elements
of the vector to `true`

when the corresponding point
was used to compute the fundamental matrix. The elements are set to `false`

if
they are not used.

`[`

additionally
returns a status code.`F`

,`inliersIndex`

,`status`

]
= estimateFundamentalMatrix(`matchedPoints1`

,`matchedPoints2`

)

`[`

uses
additional options specified by one or more Name,Value pair
arguments.`F`

,`inliersIndex`

,`status`

]
= estimateFundamentalMatrix(`matchedPoints1`

,`matchedPoints2`

,`Name,Value`

)

**Code Generation Support:**

Compile-time
constant input: `Method`

, `OutputClass`

, `DistanceType`

,
and `ReportRuntimeError`

.

Supports MATLAB^{®} Function
block: Yes.

Code Generation Support, Usage Notes, and Limitations

[1] Hartley, R., A. Zisserman, *Multiple
View Geometry in Computer Vision*, Cambridge University
Press, 2003.

[2] Rousseeuw, P., A. Leroy, *Robust
Regression and Outlier Detection*, John Wiley & Sons,
1987.

[3] Torr, P. H. S., and A. Zisserman, *MLESAC:
A New Robust Estimator with Application to Estimating Image Geometry*,
Computer Vision and Image Understanding, 2000.

`cameraPose`

| `detectFASTFeatures`

| `detectHarrisFeatures`

| `detectMinEigenFeatures`

| `detectMSERFeatures`

| `detectSURFFeatures`

| `epipolarline`

| `estimateUncalibratedRectification`

| `extractFeatures`

| `matchFeatures`

Was this topic helpful?